Diagnosis of melanoma and solar lentigo by nucleic acid analysis

ABSTRACT

The present invention provides methods for diagnosing melanoma and/or solar lentigo in a subject by analyzing nucleic acid molecules obtained from the subject. The present invention also provides methods for distinguishing melanoma from solar lentigo and/or dysplastic nevi and/or normal pigmented skin. The methods include analyzing expression or mutations in epidermal samples, of one or more skin markers. The methods can include the use of a microarray to analyze gene or protein profiles from a sample.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No. 16/522,291, filed Jul. 25, 2019 (now U.S. Pat. No. 11,332,795, issued on May 17, 2022); which is a continuation of U.S. application Ser. No. 14/832,966, filed Aug. 21, 2015, (now U.S. Pat. No. 10,407,729, issued on Sep. 10, 2019); which is a continuation of U.S. application Ser. No. 14/172,784, filed Feb. 4, 2014; (now abandoned); which is a continuation of U.S. application Ser. No. 12/991,685, filed Mar. 14, 2011; (now abandoned); which is a U.S. National Stage application of International Application No. PCT/US2009/044035, filed May 14, 2009; which claims the benefit under 35 USC § 119(e) to U.S. Application Ser. No. 61/058,149, filed Jun. 2, 2008; U.S. Application Ser. No. 61/053,988, filed May 16, 2008, and U.S. Application Ser. No. 61/127,731, filed May 14, 2008. The disclosure of each of the prior applications is considered part of and is incorporated by reference in the disclosure of this application in their entireties.

FIELD OF THE INVENTION

The invention relates generally to methods of characterizing pigmented skin lesions suspected of being melanomas using primarily non-invasive skin sampling.

BACKGROUND INFORMATION

Melanoma is a serious form of skin cancer in humans. It arises from the pigment cells (melanocytes), usually in the skin. The incidence of melanoma is increasing at the fastest rate of all cancers in the United States with a lifetime risk of 1 in 68. Although melanoma accounts for only 4% of all dermatologic cancers, it is responsible for 80% of all deaths from skin cancers. It has long been realized that recognition and diagnosis of melanoma, when it is early stage disease, is key to its cure.

Given this, it is imperative that research be carried out not only on therapeutics for melanoma, but also on all aspects of melanoma including prevention and detection. Most of these deaths from melanoma could have been prevented if the melanomas, initially located on the skin, could have been detected in their early stages. The ability to cure melanoma in its earliest skin stage, in situ, is virtually 100% if the melanoma is adequately surgically excised. If the melanoma is caught in a later stage, where it has invaded to a depth of 4 mm or more, the ten-year survival rate is less than 50%. If the melanoma is not detected until it has spread to distant parts of the body (Stage IV), the prognosis is dismal, with only 7-9% of patients surviving 5 years, with the median survival time being 8-9 months. The long-term “cure” rate for Stage IV melanoma is only 1-2%.

To advance early detection of melanoma, several things must be improved. People need to be better educated with regards to the risks of melanoma and how to prevent and detect it on their own skin. Also physicians need to be more alert to the possibility of melanoma and be better trained in detection. But even if these two areas are improved, the diagnosis of melanoma on the skin is still difficult. Studies have shown that even expert clinicians working in pigmented lesion clinics where melanoma is their specialty are only able to determine whether a suspicious pigmented lesion is melanoma or not with 60-80% sensitivity. This leads to the need for surgical biopsy of large numbers of pigmented lesions for every melanoma that is detected, and, doubtless, to the missing of some melanomas in their early stages.

In current practice melanoma is diagnosed by biopsy and histopathological examination; approximately 20 to 30 biopsies must be performed to find one melanoma and even then some melanomas are missed in the earliest stage. The limitations of visual detection are apparent to dermatologists who are constantly searching for ways to better determine whether suspicious lesions are melanoma or not without having to cut them out first. To this end, epiluminescence microscopy (ELM) has come into use. This is a method whereby lesions are looked at using a device that simultaneously magnifies the lesion while reducing visual interference from refractive index differences at the skin-air interface. While ELM does give a different view, it is of limited improvement. Studies have shown that until one becomes fairly skilled in utilizing the instrument, sensitivity in detection of melanoma actually decreases. Even very skilled users of ELM improve their ability to detect melanomas only by 5-10%. This still leads to an unacceptable sensitivity in detection and the need to biopsy large numbers of benign lesions to detect a few melanomas. And again, some melanomas will be missed completely in their early stages.

Clearly there is a need for further development of technology that will enable physicians to determine the nature and extent of suspicious lesions of the skin. Such technology would ideally directly assay the physiology of the suspect lesion to enable a sensitive diagnosis.

SUMMARY OF THE INVENTION

The present invention is based, in part, on the discovery that analysis of nucleic acid molecules or of protein expression products of nucleic acid molecules from specific genes can be used to characterize skin lesions in a subject. The method provides valuable genetic information based on DNA, messenger RNA, or protein expression products obtained therefrom, for example.

In one embodiment, the method involves use of a non-invasive approach for recovering nucleic acids such as DNA or messenger RNA or proteins from the surface of skin via a tape stripping procedure that permits a direct quantitative and qualitative assessment of biomarkers. Although tape-harvested nucleic acid and protein expression products are shown to be comparable in quality and utility to recovering such molecules by biopsy, the non-invasive method provides information regarding cells of the outermost layers of the skin that may not be obtained using biopsy samples. Finally, the non-invasive method is far less traumatic than a biopsy.

Thus, the non-invasive method is used to capture cells on pigmented skin lesions that are suspected of being melanomas. Nucleic acid molecules obtained from skin cells captured by the non-invasive method are analyzed in order to diagnose the nature of the lesion (e.g., malignant melanoma). In one embodiment, a nucleic acid molecule is amplified prior to analysis. Secondary outcomes could include tests for diagnosis and prognosis of a variety of pigmented skin lesions and even to predict a therapeutic regimen. In another embodiment, the skin cells are lysed to extract one or more proteins, which are then quantitated to diagnose the nature of the lesion. It should be understood that the methods of the invention are not limited to non-invasive techniques for obtaining skin samples. For example, but not by limitation, one of skill in the art would know other techniques for obtaining a skin sample such as scraping of the skin, biopsy, suction, blowing and other techniques. As described herein, non-invasive tape stripping is an illustrative example for obtaining a skin sample.

In another embodiment, the methods involve detection of one or more mutations in the nucleic acid sequence of the nucleic acid molecule obtained from the skin. Such mutations may be a substitution, a deletion, and/or an insertion of the nucleic acid sequence that results in a diseased state in the subject from which the skin sample is obtained.

In one embodiment, the nucleic acid molecule analyzed is listed in Tables 10-12 and 15. In another embodiment, the method further includes analyzing one or more nucleic acid molecules listed Tables 1-8. For example, in one embodiment, the gene analyzed is any one or more of interferon regulatory factor 6, claudin 23, melan-A, osteopetrosis associated transmembrane protein 1, RAS-like family 11 member B, actinin alpha 4, transmembrane protein 68, Glycine-rich protein (GRP3S), Transcription factor 4, hypothetical protein FLJ20489, cytochrome c somatic, transcription factor 4, Forkhead box P1, transducer of ERBB2-2, glutaminyl-peptide cyclotransferase (glutaminyl cyclase), hypothetical protein FLJ10770, selenophosphate synthetase 2, embryonal Fyn-associated substrate, Kruppel-like factor 8, Discs large homolog 5 (Drosophila), regulator of G-protein signalling 10, ADP-ribosylation factor related protein 2, TIMP metallopeptidase inhibitor 2, 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase, similar to RIKEN cDNA 5730421E18 gene, Regulator of G-protein signalling 10, Nuclear RNA-binding protein putative, tyrosinase-related protein 1, TIMP metallopeptidase inhibitor 2, Claudin 1, transcription factor 4, solute carrier family 16 (monocarboxylic acid transporters) member 6 (similar to solute carrier family 16 member 6; monocarboxylate transporter 6), or any combination thereof. In another embodiment, the nucleic acid molecule is from one or more genes listed in Tables 10-12 and 15.

Accordingly, provided herein is a method for characterizing and/or diagnosing melanoma in a subject, including obtaining a nucleic acid molecule or protein by biopsy of a skin lesion on the subject, and analyzing the nucleic acid molecule to distinguish melanoma from dysplastic nevi and/or normal pigmented skin in the subject. In this method, at least one nucleic acid molecule whose expression is informative of melanoma is detected in the epidermal sample. In one example, expression of one or more of the genes listed in Tables 1-8, 10-12, 15, or a combination thereof, is detected in the epidermal sample to characterize the melanoma. In one embodiment, the gene is any one or more of interferon regulatory factor 6, claudin 23, melan-A, osteopetrosis associated transmembrane protein 1, RAS-like family 11 member B, actinin alpha 4, transmembrane protein 68, Glycine-rich protein (GRP3S), Transcription factor 4, hypothetical protein FLJ20489, cytochrome c somatic, transcription factor 4, Forkhead box P1, transducer of ERBB2-2, glutaminyl-peptide cyclotransferase (glutaminyl cyclase), hypothetical protein FLJ10770, selenophosphate synthetase 2, embryonal Fyn-associated substrate, Kruppel-like factor 8, Discs large homolog 5 (Drosophila), regulator of G-protein signalling 10, ADP-ribosylation factor related protein 2, TIMP metallopeptidase inhibitor 2, 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase, similar to RIKEN cDNA 5730421E18 gene, Regulator of G-protein signalling 10, Nuclear RNA-binding protein putative, tyrosinase-related protein 1, TIMP metallopeptidase inhibitor 2, Claudin 1, transcription factor 4, solute carrier family 16 (monocarboxylic acid transporters) member 6 (similar to solute carrier family 16 member 6; monocarboxylate transporter 6), or any combination thereof.

The non-invasive methods of the invention involve applying an adhesive tape to a target area of skin in a manner sufficient to isolate a sample adhering to the adhesive tape, wherein the sample includes nucleic acid molecules or proteins. Typically, at least one nucleic acid molecule or protein whose expression is informative of melanoma is detected in the sample. The method of characterizing skin using tape stripping has a number of applications, such as the following: (i) disease classification/subclassification; (ii) monitoring disease severity and progression; (iii) monitoring treatment efficacy; and (iv) prediction of a particular treatment regimen. All of these applications, which themselves represent embodiments disclosed herein, preferably use non-invasive sampling to recover information that is otherwise difficult or impractical to recover (e.g., through the use of biopsies). The information may be contained in the DNA, protein, or RNA of skin cells close to the surface of the skin. In one embodiment, expression of one or more of the genes listed in Tables 1-8, 10-12, 15, or a combination thereof, is detected in the sample to characterize the sample. This exemplary method is particularly useful for distinguishing melanoma from dysplastic nevi and/or normal pigmented skin. In one embodiment, expression of one or more of the genes listed in Table 12 or 15 is detected in the sample to characterize the sample.

As such, also provided herein is a method for distinguishing solar lentigines from dysplastic nevi and/or basal cell carcinoma and/or normal pigmented skin in a subject, including applying an adhesive tape to a target area of skin in a manner sufficient to isolate a sample adhering to the adhesive tape, wherein the sample includes nucleic acid molecules. At least one nucleic acid molecule whose expression is informative of solar lentigo is detected in the sample. In one embodiment, expression of one or more of the genes listed in Tables 10-12, 15, or a combination thereof, is detected in the sample to characterize the melanoma. In another embodiment, expression of one or more of the genes listed in Table 12 or 15 is detected in the sample to characterize the solar lentigo.

Other embodiments are based in part on the discovery that for tape stripping of the skin, non-polar, pliable, adhesive tapes, especially pliable tapes with rubber adhesive, are more effective than other types of adhesive tapes. In some embodiments, the tape comprises a rubber adhesive on a polyurethane film. Using pliable tapes with rubber adhesives, as few as 10 or less tape strippings and in certain examples as few as 4 or even 1 tape stripping can be used to isolate and/or detect nucleic acid molecules from the epidermal layer of the skin.

In another embodiment, the methods of the invention provide for characterization of a skin lesion in situ, including application of a detectably labeled probe directly to a skin lesion for visual analysis. At least one nucleic acid molecule whose expression is informative of melanoma or dysplastic nevi or normal skin is detected on the skin lesion or surrounding margin or tissue using a specific probe. In one example, expression of one or more of the genes listed in Tables 1-8, 10-12, 15, or a combination thereof, is detected on the skin lesion or surrounding margin or tissue to characterize the melanoma. In one embodiment, expression of one or more of the genes listed in Tables 10-12 or 15 is detected in the sample to characterize the melanoma.

Also provided herein is a method for diagnosing a disease state by establishing a gene expression pattern of a target area suspected of being melanoma on the skin of a subject and comparing the subject's gene expression profile to a reference gene expression profile obtained from a corresponding normal skin sample. In one embodiment, the target area of the skin simultaneously expresses a plurality of genes at the protein level that are markers for melanoma. In another embodiment, the genes are listed in Tables 1-8, 10-12, 15, or any combination thereof. In another embodiment, the genes are listed in Tables 8 or 12.

In one embodiment, the method of diagnosing a disease state involves detection of one or more mutations in the nucleic acid sequence of the gene. Such mutations may be a substitution, a deletion, and/or an insertion of the nucleic acid sequence that results in a diseased state in the subject from which the skin sample is obtained. In one embodiment, the genes are listed in Tables 1-8, 10-12, 15, or any combination thereof. In another embodiment, the genes are listed in Tables 8 or 12.

In another aspect, the invention provides kits for characterizing a skin lesion in a subject. In one embodiment, the kit includes a skin sample collection device, such as a biopsy needle or an adhesive tape for non-invasive tape stripping, and one or more probes or primers that selectively bind to one or more nucleic acid molecules in any of Tables 1-8 and 10-12, 15, or to a nucleic acid or protein expression product of a nucleic acid molecule in any of Tables 1-8, 10-12, and 15. For example, in one embodiment, the gene analyzed is any one or more of interferon regulatory factor 6, claudin 23, melan-A, osteopetrosis associated transmembrane protein 1, RAS-like family 11 member B, actinin alpha 4, transmembrane protein 68, Glycine-rich protein (GRP3S), Transcription factor 4, hypothetical protein FLJ20489, cytochrome c somatic, transcription factor 4, Forkhead box P1, transducer of ERBB2-2, glutaminyl-peptide cyclotransferase (glutaminyl cyclase), hypothetical protein FLJ10770, selenophosphate synthetase 2, embryonal Fyn-associated substrate, Kruppel-like factor 8, Discs large homolog 5 (Drosophila), regulator of G-protein signalling 10, ADP-ribosylation factor related protein 2, TIMP metallopeptidase inhibitor 2, 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase, similar to RIKEN cDNA 5730421E18 gene, Regulator of G-protein signalling 10, Nuclear RNA-binding protein putative, tyrosinase-related protein 1, TIMP metallopeptidase inhibitor 2, Claudin 1, transcription factor 4, solute carrier family 16 (monocarboxylic acid transporters) member 6 (similar to solute carrier family 16 member 6; monocarboxylate transporter 6), or any combination thereof. In another embodiment, the kit includes a microarray containing at least a fragment of a gene or a nucleic acid or protein product of a gene identified in any of Tables 1-8, 10-12, 15, or any combination thereof.

In another embodiment, the kit for characterizing a skin lesion in a subject includes an applicator and one or more probes or primers that selectively bind to one or more nucleic acid molecules in any of Tables 1-8 and 10-12, 15, or to a nucleic acid or protein expression product of a nucleic acid molecule in any of Tables 1-8, 10-12, and 15. In one embodiment, the probes are detectably labeled for visual identification of expression of RNA.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are graphical diagrams showing data from the EDR, PTP, and PTN as a function of sample size, assuming a threshold for declaring the significance of a probe/gene expression difference between nevi and primary melanoma of p<0.05.

FIGS. 2A and 2B are graphical diagrams showing data from a sample size analysis that considered the contrast results for nevi vs. primary melanoma in the context of an analysis of variance (ANOVA) comparing normal skin, nevi, and primary melanoma

FIGS. 3A and 3B are graphical diagrams showing data from an analysis focusing exclusively on the posterior true probability (PTP) for different assumed significance levels.

FIGS. 4A to 4D are pictorial and graphical diagrams showing the development of a gene classifier for distinguishing melanoma from atypical nevi and normal pigmented skin.

FIGS. 5A and 5B are graphical diagrams showing data from prediction analysis of the developed classifiers for distinguishing melanoma from atypical nevi and normal pigmented skin.

FIGS. 6A to 6E are graphical diagrams showing data from prediction analysis of the developed classifiers for distinguishing melanoma from atypical nevi and normal pigmented skin.

FIG. 7 is a hierarchial cluster analysis of the identified genes distinguishing melanoma from atypical nevi and normal pigmented skin.

FIG. 8 is a graphical diagram showing results from classification modeling of the identified genes.

FIG. 9 is a graphical diagram showing data of a developed classifier for distinguishing melanoma from atypical nevi and normal pigmented skin.

FIG. 10 is a pictorial diagram showing the development of a classifier to discriminate melanoma from atypical nevi using non-invasive tape strip-based genomic profiling.

FIG. 11 is a pictorial diagram describing the development of a 19-gene classifier that discriminates melanoma from atypical nevi.

FIG. 12 is a pictorial diagram showing a hierarchial cluster analysis of the identified genes from the 19-gene classifier identified in FIG. 11 .

FIG. 13 is a pictorial diagram showing results from 10 melanoma and 10 nevi samples against the 19-gene classifier identified in FIG. 11 .

FIG. 14 is a graphical diagram showing data of a developed classifier for distinguishing solar lentigines from normal pigmented skin.

FIG. 15 is a hierarchial cluster analysis of the identified genes from FIG. 14 distinguishing solar lentigines from normal pigmented skin.

FIG. 16 is a graphical diagram showing data from prediction analysis of the developed classifiers for distinguishing solar lentigines from normal pigmented skin.

FIG. 17 is a hierarchial cluster analysis of a gene expression profile distinguishing solar lentigines from atypical nevi and basal cell carcinoma.

FIG. 18 is a hierarchial cluster analysis of a gene expression profile distinguishing solar lentigines from lentigo maligna.

FIG. 19 is a hierarchial cluster analysis of a 28-gene classifier distinguishing solar lentigines from lentigo maligna.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is based, in part, on the discovery that analysis of nucleic acid molecules or of protein expression products of nucleic acid molecules from specific genes can be used to characterize skin lesions in a subject. Accordingly, the present invention provides methods and kits useful for detecting cancer, especially melanoma, by determining the expression profiles of one or more specific genes of interest. In addition, the present invention provides methods and kits useful for distinguishing solar lentigines from cancer by determining the expression profiles of one or more specific genes of interest.

There are two main motivations for conducting genome wide expression profiling studies in melanoma. First, melanoma is one of the best characterized carcinogenesis models for gradual progression of benign lesions to cancer: normal pigmented cells to nevi to atypical nevi to primary melanoma in situ to invasive primary melanoma to aggressive metastatic melanoma. This progression is known to correlate with distinctive chromosomal changes, and is thought to be mediated by stepwise progressive changes in gene expression, suggesting that expression profiling may identify genes responsible for tumorigenesis in melanoma. Indeed, candidate tumor genes have been identified with microarray analyses of melanoma cell lines. The second reason is that molecular characterization of tumors may allow a better staging classification of tumors and prognosis prediction. While histological characteristics such as the thickness and ulceration of tumors have some value as predictors of prognosis, there is lack of informative markers that help determine which patients will do well and which patients will have progressive disease and metastasis. Molecular markers identified in microarray experiments of tumors are already being introduced into clinical practice in the management of breast cancer. Gene expression profiling experiments in melanoma and melanoma cell lines suggest that the classification of melanoma can be improved, but studies are lacking with sufficient power to define molecular criteria for diagnosis or identify prognostic markers; the establishments of such markers would represent a major advance in melanoma care. A major reason for the lack of powerful microarray studies in melanoma is that, unlike most solid tumors, it is necessary to paraffin embed and section the whole lesion for histology, leaving no sample for RNA isolation. Although this situation is now changing, the ability to avoid biopsy until a definitive diagnosis is made would be powerful for subjects that would not normally be eligible for one or more biopsies.

As used in this specification and the appended claims, the singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. Thus, for example, references to “the method” includes one or more methods, and/or steps of the type described herein which will become apparent to those persons skilled in the art upon reading this disclosure and so forth.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the invention, the preferred methods and materials are now described.

The term “subject” as used herein refers to any individual or patient to which the subject methods are performed. Generally the subject is human, although as will be appreciated by those in the art, the subject may be an animal. Thus other animals, including mammals such as rodents (including mice, rats, hamsters and guinea pigs), cats, dogs, rabbits, farm animals including cows, horses, goats, sheep, pigs, etc., and primates (including monkeys, chimpanzees, orangutans and gorillas) are included within the definition of subject.

As used herein, the terms “sample” and “biological sample” refer to any sample suitable for the methods provided by the present invention. A sample of cells can be any sample, including, for example, a skin sample obtained by non-invasive tape stripping or biopsy of a subject, or a sample of the subject's bodily fluid. Thus, in one embodiment, the biological sample of the present invention is a tissue sample, e.g., a biopsy specimen such as samples from needle biopsy. In one embodiment, the term “sample” refers to any preparation derived from skin of a subject. For example, a sample of cells obtained using the non-invasive method described herein can be used to isolate nucleic acid molecules or proteins for the methods of the present invention. Samples for the present invention typically are taken from a skin lesion, which is suspected of being the result of a disease or a pathological or physiological state, such as psoriasis or dermatitis, or the surrounding margin or tissue. As used herein, “surrounding margin” or “surrounding tissue” refers to tissue of the subject that is adjacent to the skin lesion, but otherwise appears to be normal or free from lesion.

As used herein “corresponding normal cells” or “corresponding normal sample” refers to cells or a sample from a subject that is from the same organ and of the same type as the cells being examined. In one aspect, the corresponding normal cells comprise a sample of cells obtained from a healthy individual that does not have a skin lesion or skin cancer. Such corresponding normal cells can, but need not be, from an individual that is age-matched and/or of the same sex as the individual providing the cells being examined. Thus, the term “normal sample” or “control sample” refers to any sample taken from a subject of similar species that is considered healthy or otherwise not suffering from the particular disease, pathological or physiological state, or from the same subject in an area free from skin lesions. As such, a normal/standard level of RNA denotes the level of RNA present in a sample from the normal sample. A normal level of RNA can be established by combining skin samples or cell extracts taken from normal healthy subjects and determining the level of one or more RNAs present. In addition, a normal level of RNA also can be determined as an average value taken from a population of subjects that is considered to be healthy, or is at least free of a particular disease, pathological or physiological state. Accordingly, levels of RNA in subject, control, and disease samples can be compared with the standard values. Deviation between standard and subject values establishes the parameters for diagnosing or characterizing disease.

The term “skin” refers to the outer protective covering of the body, consisting of the epidermis (including the stratum corneum) and the underlying dermis, and is understood to include sweat and sebaceous glands, as well as hair follicle structures. Throughout the present application, the adjective “cutaneous” can be used, and should be understood to refer generally to attributes of the skin, as appropriate to the context in which they are used. The epidermis of the human skin comprises several distinct layers of skin tissue. The deepest layer is the stratum basalis layer, which consists of columnar cells. The overlying layer is the stratum spinosum, which is composed of polyhedral cells. Cells pushed up from the stratum spinosum are flattened and synthesize keratohyalin granules to form the stratum granulosum layer. As these cells move outward, they lose their nuclei, and the keratohyalin granules fuse and mingle with tonofibrils. This forms a clear layer called the stratum lucidum. The cells of the stratum lucidum are closely packed. As the cells move up from the stratum lucidum, they become compressed into many layers of opaque squamae. These cells are all flattened remnants of cells that have become completely filled with keratin and have lost all other internal structure, including nuclei. These squamae constitute the outer layer of the epidermis, the stratum corneum. At the bottom of the stratum corneum, the cells are closely compacted and adhere to each other strongly, but higher in the stratum they become loosely packed, and eventually flake away at the surface.

As used herein, the term “skin lesion” refers to a change in the color or texture in an area of skin. As such, “skin lesions suspected of being melanoma” are skin lesions with characteristics of malignant melanoma, which are well known to those of skill in the art, such as dermatologists and oncologists. Such lesions are sometimes raised and can have a color that is different from the color of normal skin of an individual (e.g., brown, black, red, or blue). Lesions suspected of being melanoma sometimes include a mixture of colors, are often asymmetrical, can change in appearance over time, and may bleed. A skin lesion suspected of being melanoma may be a mole or nevus. Melanoma lesions are usually, but not always, larger than 6 mm in diameter. Melanoma includes superficial spreading melanoma, nodular melanoma, acral lentiginous melanoma, and lentigo maligna melanoma. The term “lentigo maligna” refers to a precancerous lesion on the skin, especially in areas exposed to the sun, that is flat, mottled, and brownish with an irregular outline and grows slowly over a period of years. Melanoma can occur on skin that has been overexposed to the sun. Therefore, in one embodiment the skin sample is taken from an area of skin that has been overexposed to the sun.

The term “dysplastic nevus” refers to an atypical mole or a mole whose appearance is different from that of common moles. Dysplastic nevi are generally larger than ordinary moles and have irregular and indistinct borders. Their color frequently is not uniform and ranges from pink to dark brown; they usually are flat, but parts may be raised above the skin surface. Dysplastic naevus can be found anywhere, but are most common on the trunk of a subject.

The term “cancer” as used herein, includes any malignant tumor including, but not limited to, carcinoma and sarcoma. Cancer arises from the uncontrolled and/or abnormal division of cells that then invade and destroy the surrounding tissues. As used herein, “proliferating” and “proliferation” refer to cells undergoing mitosis. As used herein, “metastasis” refers to the distant spread of a malignant tumor from its sight of origin. Cancer cells may metastasize through the bloodstream, through the lymphatic system, across body cavities, or any combination thereof. The term “cancerous cell” as provided herein, includes a cell afflicted by any one of the cancerous conditions provided herein. The term “carcinoma” refers to a malignant new growth made up of epithelial cells tending to infiltrate surrounding tissues, and to give rise to metastases. The term “melanoma” refers to a malignant tumor of melanocytes which are found predominantly in skin but also in bowel and the eye. “Melanocytes” refer to cells located in the bottom layer, the basal lamina, of the skin's epidermis and in the middle layer of the eye. Thus, “melanoma metastasis” refers to the spread of melanoma cells to regional lymph nodes and/or distant organs (e.g., liver, brain, breast, prostate, etc.).

The term “basal cell carcinoma” or “BCC” refers to a slow-growing neoplasm that is locally invasive but rarely metastasizes. It is derived from basal cells, the deepest layer of epithelial cells of the epidermis or hair follicles. BCC is a common skin cancer that is often associated with overexposure to sunlight.

The term “solar lentigo” or “solar lentigines,” also known as a sun-induced freckle or senile lentigo, is a dark (hyperpigmented) lesion caused by natural or artificial ultraviolet (UV) light. Solar lentigines may be single or multiple. Solar lentigines are benign, but they do indicate excessive sun exposure, a risk factor for the development of skin cancer. The lesions tend to increase in number with age, making them common among the middle age and older population. They can vary in size from about 0.2 to 2.0 cm. These flat lesions usually have discrete borders, are dark in color, and have an irregular shape.

As used herein, the term “gene” refers to a linear sequence of nucleotides along a segment of DNA that provides the coded instructions for synthesis of RNA, which, when translated into protein, leads to the expression of hereditary character. As such, the term “skin marker” or “biomarker” refers to a gene whose expression level is different between skin surface samples at the site of malignant melanoma and skin surface samples of normal skin or a lesion, which is benign, such as a benign nevus. Therefore, expression of a melanoma skin marker of the invention is related to, or indicative of, melanoma. Many statistical techniques are known in the art, which can be used to determine whether a statistically significant difference in expression is observed at a high (e.g., 90% or 95%) confidence level. As such, an increase or decrease in expression of these genes is related to and can characterize malignant melanoma. In one embodiment, there is at least a two-fold difference in levels between skin sample near the site of malignant melanoma and skin samples from normal skin.

As used herein, the term “nucleic acid molecule” means DNA, RNA, single-stranded, double-stranded or triple stranded and any chemical modifications thereof. Virtually any modification of the nucleic acid is contemplated. A “nucleic acid molecle” can be of almost any length, from 10, 20, 30, 40, 50, 60, 75, 100, 125, 150, 175, 200, 225, 250, 275, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000, 7000, 8000, 9000, 10,000, 15,000, 20,000, 30,000, 40,000, 50,000, 75,000, 100,000, 150,000, 200,000, 500,000, 1,000,000, 1,500,000, 2,000,000, 5,000,000 or even more bases in length, up to a full-length chromosomal DNA molecule. For methods that analyze expression of a gene, the nucleic acid isolated from a sample is typically RNA.

Micro-RNAs (miRNA) are small single stranded RNA molecules an average of 22 nucleotides long that are involved in regulating mRNA expression in diverse species including humans (reviewed in Bartel 2004). The first report of miRNA was that of the lin-4 gene, discovered in the worm C. elegans (Lee, Feinbaum et al. 1993). Since then hundreds of miRNAs have been discovered in flies, plants and mammals. miRNAs regulate gene expression by binding to the 3′-untranslated regions of mRNA and catalyze either i) cleavage of the mRNA; or 2) repression of translation. The regulation of gene expression by miRNAs is central to many biological processes such as cell development, differentiation, communication, and apoptosis (Reinhart, Slack et al. 2000; Baehrecke 2003; Brennecke, Hipfner et al. 2003; Chen, Li et al. 2004). Recently it has been shown that miRNA are active during embryogenesis of the mouse epithelium and play a significant role in skin morphogenesis (Yi, O'Carroll et al. 2006).

Given the role of miRNA in gene expression it is clear that miRNAs will influence, if not completely specify the relative amounts of mRNA in particular cell types and thus determine a particular gene expression profile (i.e., a population of specific mRNAs) in different cell types. In addition, it is likely that the particular distribution of specific miRNAs in a cell will also be distinctive in different cell types. Thus, determination of the miRNA profile of a tissue may be used as a tool for expression profiling of the actual mRNA population in that tissue. Accordingly, miRNA levels and/or detection of miRNA mutations are useful for the purposes of disease detection, diagnosis, prognosis, or treatment-related decisions (i.e., indicate response either before or after a treatment regimen has commenced) or characterization of a particular disease in the subject.

As used herein, the term “protein” refers to at least two covalently attached amino acids, which includes proteins, polypeptides, oligopeptides and peptides. A protein may be made up of naturally occurring amino acids and peptide bonds, or synthetic peptidomimetic structures. Thus “amino acid”, or “peptide residue”, as used herein means both naturally occurring and synthetic amino acids. For example, homo-phenylalanine, citrulline and noreleucine are considered amino acids for the purposes of the invention. “Amino acid” also includes imino acid residues such as proline and hydroxyproline. The side chains may be in either the (R) or the (S) configuration.

A “probe” or “probe nucleic acid molecule” is a nucleic acid molecule that is at least partially single-stranded, and that is at least partially complementary, or at least partially substantially complementary, to a sequence of interest. A probe can be RNA, DNA, or a combination of both RNA and DNA. It is also within the scope of the present invention to have probe nucleic acid molecules comprising nucleic acids in which the backbone sugar is other that ribose or deoxyribose. Probe nucleic acids can also be peptide nucleic acids. A probe can comprise nucleolytic-activity resistant linkages or detectable labels, and can be operably linked to other moieties, for example a peptide.

A single-stranded nucleic acid molecule is “complementary” to another single-stranded nucleic acid molecule when it can base-pair (hybridize) with all or a portion of the other nucleic acid molecule to form a double helix (double-stranded nucleic acid molecule), based on the ability of guanine (G) to base pair with cytosine (C) and adenine (A) to base pair with thymine (T) or uridine (U). For example, the nucleotide sequence 5′-TATAC-3′ is complementary to the nucleotide sequence 5′-GTATA-3′.

The term “antibody” as used in this invention is meant to include intact molecules of polyclonal or monoclonal antibodies, as well as fragments thereof, such as Fab and F(ab′)2, Fv and SCA fragments which are capable of binding an epitopic determinant. The term “specifically binds” or “specifically interacts,” when used in reference to an antibody means that an interaction of the antibody and a particular epitope has a dissociation constant of at least about 1×10⁻⁶, generally at least about 1×10⁻⁷, usually at least about 1×10⁻⁸, and particularly at least about 1×10⁻⁹ or 1×10⁻¹⁰ or less.

As used herein “hybridization” refers to the process by which a nucleic acid strand joins with a complementary strand through base pairing. Hybridization reactions can be sensitive and selective so that a particular sequence of interest can be identified even in samples in which it is present at low concentrations. In an in vitro situation, suitably stringent conditions can be defined by, for example, the concentrations of salt or formamide in the prehybridization and hybridization solutions, or by the hybridization temperature, and are well known in the art. In particular, stringency can be increased by reducing the concentration of salt, increasing the concentration of formamide, or raising the hybridization temperature. For example, hybridization under high stringency conditions could occur in about 50% formamide at about 37° C. to 42° C. Hybridization could occur under reduced stringency conditions in about 35% to 25% formamide at about 30° C. to 35° C. In particular, hybridization could occur under high stringency conditions at 42° C. in 50% formamide, 5×SSPE, 0.3% SDS, and 200 mg/ml sheared and denatured salmon sperm DNA. Hybridization could occur under reduced stringency conditions as described above, but in 35% formamide at a reduced temperature of 35° C. The temperature range corresponding to a particular level of stringency can be further narrowed by calculating the purine to pyrimidine ratio of the nucleic acid of interest and adjusting the temperature accordingly. Variations on the above ranges and conditions are well known in the art.

As used herein, the term “mutation” refers to a change in the genome with respect to the standard wild-type sequence. Mutations can be deletions, insertions, or rearrangements of nucleic acid sequences at a position in the genome, or they can be single base changes at a position in the genome, referred to as “point mutations.” Mutations can be inherited, or they can occur in one or more cells during the lifespan of an individual.

As used herein, the term “kit” or “research kit” refers to a collection of products that are used to perform a biological research reaction, procedure, or synthesis, such as, for example, a detection, assay, separation, purification, etc., which are typically shipped together, usually within a common packaging, to an end user.

As used herein, the term “ameliorating” or “treating” means that the clinical signs and/or the symptoms associated with the cancer or melanoma are lessened as a result of the actions performed. The signs or symptoms to be monitored will be characteristic of a particular cancer or melanoma and will be well known to the skilled clinician, as will the methods for monitoring the signs and conditions. Thus, a “treatment regimen” refers to any systematic plan or course for treating a disease or cancer in a subject.

Samples from a tissue can be isolated by any number of means well known in the art. Invasive methods for isolating a sample include, but are not limited to the use of needles or scalpels, for example during biopsies of various tissues. Non-invasive methods for isolating a sample include, but are not limited to tape-stripping and skin scraping.

Accordingly, in one embodiment, the present invention employs a non-invasive tape stripping technology to obtain samples of suspicious lesions. As such, DNA microarray assays are used to create a non-invasive diagnostic for melanoma and/or distinguishing melanoma from solar lentigo. Tape-stripping removes superficial cells from the surface of the skin as well as adnexal cells. Small amounts of nucleic acid molecules isolated from tape-stripped cells can be amplified and used for microarray analyses and quantitative PCR. In addition, proteins obtained from the lysed cells may be quantitated for diagnosis of disease. Consequently, tape-stripping is a non-invasive diagnostic method, which does not interfere with subsequent histological analyses, thereby bypassing a major limitation to current expression profiling studies on melanoma. While tape stripping will primarily sample superficial cells from the epidermis, this method holds great promise in the diagnoses and prognosis prediction in pigmented lesions for the following reasons: First, in contrast to benign nevi, in many melanomas the pigmented cells migrate into the epidermis and/or adnexa. Consequently, this feature may help differentiate benign pigmented lesions from melanomas based on tape stripping. Second, there are changes in the dermis and epidermis adjacent to melanoma. The epidermal hyperplasia overlying melanoma seems to correlate with both angiogenesis and metastatic potential; these changes are expected to be sampled with the tape stripping method. Finally, some advanced melanomas do reach the surface of the skin and melanoma cancer cells would be sampled directly by the tape stripping. In addition tape stripping is useful in the care of patients with multiple pigmented lesions where it is unpractical to biopsy each and every lesion. Accordingly, the present invention demonstrates that stratum corneum RNA, harvested by tape stripping with Epidermal Genetic Information Retrieval (EGIR) (see U.S. Pat. No. 6,949,338, incorporated herein by reference), can be used to distinguish melanoma from dysplastic nevi in suspicious pigmented lesions.

As indicated, the tape stripping methods provided herein typically involve applying an adhesive tape to the skin of a subject and removing the adhesive tape from the skin of the subject one or more times. In certain examples, the adhesive tape is applied to the skin and removed from the skin about one to ten times. Alternatively, about ten adhesive tapes can be sequentially applied to the skin and removed from the skin. These adhesive tapes are then combined for further analysis. Accordingly, an adhesive tape can be applied to and removed from a target site 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 time, and/or 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 adhesive tape can be applied to and removed from the target site. In one illustrative example, the adhesive tape is applied to the skin between about one and eight times, in another example, between one and five times, and in another illustrative example the tape is applied and removed from the skin four times.

The rubber based adhesive can be, for example, a synthetic rubber-based adhesive. The rubber based adhesive in illustrative examples, has high peel, high shear, and high tack. For example, the rubber based adhesive can have a peak force tack that is at least 25%, 50%, or 100% greater than the peak force tack of an acrylic-based tape such as D-SQUAME™. D-SQUAME™ has been found to have a peak force of 2 Newtons, wherein peak force of the rubber based adhesive used for methods provided herein, can be 4 Newtons or greater. Furthermore, the rubber based adhesive can have adhesion that is greater than 2 times, 5 times, or 10 times that of acrylic based tape. For example, D-SQUAME™ has been found to have adhesion of 0.0006 Newton meters, whereas the rubber based tape provided herein can have an adhesion of about 0.01 Newton meters using a texture analyzer. Furthermore, in certain illustrative examples, the adhesive used in the methods provided herein has higher peel, shear and tack than other rubber adhesives, especially those used for medical application and Duct tape.

Virtually any size and/or shape of adhesive tape and target skin site size and shape can be used and analyzed, respectively, by the methods of the present invention. For example, adhesive tape can be fabricated into circular discs of diameter between 10 millimeters and 100 millimeters, for example between 15 and 25 millimeters in diameter. The adhesive tape can have a surface area of between about 50 mm² and 1000 mm², between about 100 mm² to 500 mm² or about 250 mm².

In another embodiment, the sample is obtained by means of an invasive procedure, such as biopsy. Biopsies may be taken instead of or after tape stripping and are subjected to standard histopathologic analysis. Analysis of biopsy samples taken simultaneously with tape stripping samples may then be correlated with the data generated from one or more of analysis of selected lesion RNA samples by DNA microarray, correlation of gene expression data with histopathology, and creation of a candidate expression classifier for diagnosis of melanoma.

As used herein, “biopsy” refers to the removal of cells or tissues for analysis. There are many different types of biopsy procedures known in the art. The most common types include: (1) incisional biopsy, in which only a sample of tissue is removed; (2) excisional biopsy, in which an entire lump or suspicious area is removed; and (3) needle biopsy, in which a sample of tissue or fluid is removed with a needle. When a wide needle is used, the procedure is called a core biopsy. When a thin needle is used, the procedure is called a fine-needle aspiration biopsy. Other types of biopsy procedures include, but are not limited to, shave biopsy, punch biopsy, curettage biopsy, and in situ biopsy. In another embodiment, the skin sample is obtained by scraping the skin with an instrument to remove one or more nucleic acid molecules from the skin.

The skin sample obtained using the tape stripping method includes, epidermal cells including cells comprising adnexal structures. In certain illustrative examples, the sample includes predominantly epidermal cells, or even exclusively epidermal cells. The epidermis consists predominantly of keratinocytes (>90%), which differentiate from the basal layer, moving outward through various layers having decreasing levels of cellular organization, to become the cornified cells of the stratum corneum layer. Renewal of the epidermis occurs every 20-30 days in uninvolved skin. Other cell types present in the epidermis include melanocytes, Langerhans cells, and Merkel cells. As illustrated in the Examples herein, the tape stripping method of the present invention is particularly effective at isolating epidermal samples.

Nucleic acid molecules can also be isolated by lysing the cells and cellular material collected from the skin sample by any number of means well known to those skilled in the art. For example, a number of commercial products available for isolating polynucleotides, including but not limited to, RNeasy™ (Qiagen, Valencia, Calif.) and TriReagent™ (Molecular Research Center, Inc, Cincinnati, Ohio) can be used. The isolated polynucleotides can then be tested or assayed for particular nucleic acid sequences, including a polynucleotide encoding a cytokine. Methods of recovering a target nucleic acid molecule within a nucleic acid sample are well known in the art, and can include microarray analysis.

Nucleic acid molecules may be analyzed in any number of ways known in the art. For example, the presence of nucleic acid molecules can be detected by DNA-DNA or DNA-RNA hybridization or amplification using probes or fragments of the specific nucleic acid molecule. Nucleic acid amplification based assays involve the use of oligonucleotides or oligomers based on the nucleic acid sequences to detect transformants containing the specific DNA or RNA.

In one embodiment, analysis of the nucleic acid molecules includes genetic analysis is to determine the nucleotide sequence of a gene. Since a difference in length or sequence between DNA fragments isolated from a sample and those of known sequences are due to an insertion, deletion, or substitution of one or more nucleotides, the determination of nucleic acid sequences provides information concerning mutations which have absolute influence on the physiology of the disease state in the subject. These mutations may also include transposition or inversion and are difficult to detect by other techniques than direct sequencing. For example, it has recently been shown that the presence of the c-kit-activating mutation, L576P, is indicative of malignant melanomas (see Table 1). Accordingly, the methods of the present invention may be used to detect genetic mutations in one or more genes listed in Tables 1-8 and 10-12 for diagnosis and/or characterization of a skin lesion in a subject.

A variety of protocols for detecting and measuring the expression of nucleic acid molecules, using either polyclonal or monoclonal antibodies specific for the protein expression product are known in the art. Examples include enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), and fluorescence activated cell sorting (FACS). These and other assays are described, among other places, in Hampton, R. et al. (1990; Serological Methods, a Laboratory Manual, APS Press, St Paul, Minn.) and Maddox, D. E. et al. (1983; J. Exp. Med. 158:1211-1216).

In another embodiment, antibodies that specifically bind the expression products of the nucleic acid molecules of the invention may be used to characterize the skin lesion of the subject. The antibodies may be used with or without modification, and may be labeled by joining them, either covalently or non-covalently, with a reporter molecule.

A wide variety of labels and conjugation techniques are known by those skilled in the art and may be used in various nucleic acid and amino acid assays. Means for producing labeled hybridization or PCR probes for detecting sequences related to the nucleic acid molecules of Tables 1-8, 10-12, and 15 include oligolabeling, nick translation, end-labeling or PCR amplification using a labeled nucleotide. Alternatively, the nucleic acid molecules, or any fragments thereof, may be cloned into a vector for the production of an mRNA probe. Such vectors are known in the art, are commercially available, and may be used to synthesize RNA probes in vitro by addition of an appropriate RNA polymerase such as T7, T3, or SP6 and labeled nucleotides. These procedures may be conducted using a variety of commercially available kits (Pharmacia & Upjohn, (Kalamazoo, Mich.); Promega (Madison Wis.); and U.S. Biochemical Corp., Cleveland, Ohio). Suitable reporter molecules or labels, which may be used for ease of detection, include radionuclides, enzymes, fluorescent, chemiluminescent, or chromogenic agents as well as substrates, cofactors, inhibitors, magnetic particles, and the like.

PCR systems usually use two amplification primers and an additional amplicon-specific, fluorogenic hybridization probe that specifically binds to a site within the amplicon. The probe can include one or more fluorescence label moieties. For example, the probe can be labeled with two fluorescent dyes: 1) a 6-carboxy-fluorescein (FAM), located at the 5′-end, which serves as reporter, and 2) a 6-carboxy-tetramethyl-rhodamine (TAMRA), located at the 3′-end, which serves as a quencher. When amplification occurs, the 5′-3′ exonuclease activity of the Taq DNA polymerase cleaves the reporter from the probe during the extension phase, thus releasing it from the quencher. The resulting increase in fluorescence emission of the reporter dye is monitored during the PCR process and represents the number of DNA fragments generated. In situ PCR may be utilized for the direct localization and visualization of target nucleic acid molecules and may be further useful in correlating expression with histopathological finding.

Means for producing specific hybridization probes for nucleic acid molecules of the invention include the cloning of the nucleic acid sequences into vectors for the production of mRNA probes. Such vectors are known in the art, commercially available, and may be used to synthesize RNA probes in vitro by means of the addition of the appropriate RNA polymerases and the appropriate labeled nucleotides. Hybridization probes may be labeled by a variety of reporter groups, for example, radionuclides such as ³²P or ³⁵S, or enzymatic labels, such as alkaline phosphatase coupled to the probe via avidin/biotin coupling systems, and the like.

In order to provide a basis for the diagnosis or characterization of disease associated with expression of the nucleic acid molecules of the invention, a normal or standard profile for expression is established. Standard hybridization may be quantified by comparing the values obtained from subjects of known skin characterization (e.g., from subjects either having melanoma, having dysplastic nevi, and/or having solar lentigines). Standard values obtained from such samples may be compared with values obtained from samples from subjects having skin lesions that are suspected of being melanoma. Deviation between standard and subject values is used to establish the presence of disease.

Accordingly, in one aspect of the invention, a non-invasive sampling method is provided for the characterization of skin lesion on the skin. In one embodiment, a sample set of pigmented skin lesions is created. Each sample consists of nucleic acid molecules recovered by tape stripping or biopsy sample of the superficial epidermis overlying the lesion. In addition to tape striping, a standard biopsy of the same lesion may also be performed, along with accompanying histology and diagnosis. Nucleic acid molecules recovered by tape stripping the superficial epidermis of normal skin will serve as a negative control.

In another aspect, the invention provides a method of distinguishing melanoma from solar lentigo and/or dysplastic nevi and/or normal pigmented skin in a subject. In one embodiment, the method includes analyzing a nucleic acid molecule from one or more genes listed in any of Tables 1-8, 10-12, 15, or any combination thereof. A target area of the skin of a subject that suspected of being melanoma is assayed for expression of a large number of genes. Analyzing expression includes any qualitative or quantitative method for detecting expression of a gene, many of which are known in the art. The method can include analyzing expression of specific markers by measuring expression of the markers using a quantitative method, or by using a qualitative method. Non-limiting methods for analyzing polynucleotides and polypeptides are discussed below.

In another aspect, the invention provides a method of distinguishing solar lentigines from dysplastic nevi and/or basal cell carcinoma and/or normal pigmented skin in a subject. In one embodiment, the method includes analyzing a nucleic acid molecule from one or more genes listed in any of Tables 1-8, 10-12, 15, or any combination thereof. A target area of the skin of a subject that suspected of being melanoma is assayed for expression of a large number of genes. Analyzing expression includes any qualitative or quantitative method for detecting expression of a gene, many of which are known in the art. The method can include analyzing expression of specific markers by measuring expression of the markers using a quantitative method, or by using a qualitative method. Non-limiting methods for analyzing polynucleotides and polypeptides are discussed below

Methods of analyzing expression of a gene of the present invention can utilize a microarray, or other miniature high-throughput technology, for detecting expression of one or more gene products. Quantitative measurement of expression levels using such microarrays is also known in the art, and typically involves a modified version of a traditional method for measuring expression as described herein. For example, such quantitation can be performed by measuring a phosphor image of a radioactive-labeled probe binding to a spot of a microarray, using a phospohor imager and imaging software.

In a related aspect, the invention provides a method for diagnosing various disease states in a subject by identifying new diagnostic markers, specifically the classification and diagnosis of melanoma. In addition, the invention provides a method for distinguishing solar lentigines from dysplastic nevi and/or lentigo maligna and/or normal skin. Thus, the invention provides a method for diagnosing various disease states in a subject by identifying new diagnostic markers, specifically the classification and diagnosis of melanoma. By identifying gene sets that are unique to a given state, these differences in the genetic expression can be utilized for diagnostic purposes. In one embodiment, the nucleic acid molecule is RNA, including messenger RNA (mRNA) that is isolated from a sample from the subject. Up-regulated and down-regulated gene sets for a given disease state may be subsequently combined. The combination enables those of skill in the art to identify gene sets or panels that are unique to a given disease state. Such gene sets are of immense diagnostic value as they can be routinely used in assays that are simpler than microarray analysis (for example “real-time” quantitative PCR). Such gene sets also provide insights into pathogenesis and targets for the design of new drugs.

A reference database containing a number of reference projected profiles is also created from skin samples of subjects with known states, such as normal (i.e., non-melanoma) and various skin cancer disease states and/or pigmented non-cancer states. The projected profile is then compared with the reference database containing the reference projected profiles. If the projected profile of the subject matches best with the profile of a particular disease state in the database, the subject is diagnosed as having such disease state. Various computer systems and software can be utilized for implementing the analytical methods of this invention and are apparent to one of skill in the art. Exemplary software programs include, but are not limited to, Cluster & TreeView (Stanford, URLs: rana.lbl.gov or microarray.org), GeneCluster (MIT/Whitehead Institute, URL: MPR/GeneCluster/GeneCluster.html), Array Explorer (SpotFire Inc, URL: spotfire.com/products/scicomp.asp#SAE) and GeneSpring (Silicon Genetics Inc, URL: sigenetics.com/Products/GeneSpring/index.html) (for computer systems and software, see also U.S. Pat. No. 6,203,987, incorporated herein by reference).

In another aspect, the methods of the present invention involve in situ analysis of the skin lesion for characterization thereof. For in situ methods, nucleic acid molecules do not need to be isolated from the subject prior to analysis. In one embodiment, detectably labeled probes are contacted with a cell or tissue of a subject for visual detection of expressed RNA to characterize the skin lesion.

In another aspect, the methods of the present invention can also be useful for monitoring the progression of diseases and the effectiveness of treatments. For example, by comparing the projected profile prior to treatment with the profile after treatment. In one embodiment, the method characterizes a cancer as melanoma metastasis based on analysis of one or more nucleic acid molecules from Tables 1-8. In another embodiment, the method characterizes a solar lentigo based on analysis of one or more nucleic acid molecules from Tables 10-12 and 15. It is known that in many cases, by the time a diagnosis of melanoma is established in a subject, metastasis has already occurred since melanomas contain multiple cell populations characterized by diverse growth rates, karyotypes, cell-surface properties, antigenicity, immunogenicity, invasion, metastasis, and sensitivity to cytotoxic drugs or biologic agents. Thus, the present invention may be used to characterize cancer of an organ as having metastasized from melanoma.

In a related aspect, the methods of the present invention can also be useful for determining an appropriate treatment regimen for a subject having a specific cancer or melanoma. In another related aspect, the methods of the present invention can also be useful for determining an appropriate treatment regimen for a subject having solar lentigo. Thus, the methods of the invention are useful for providing a means for practicing personalized medicine, wherein treatment is tailored to a subject based on the particular characteristics of the cancer or skin lesion in the subject. The method can be practiced, for example, by first determining whether the skin lesion is melanoma or solar lentigo, as described above.

The sample of cells examined according to the present method can be obtained from the subject to be treated, or can be cells of an established cancer cell line of the same type as that of the subject. In one aspect, the established cell line can be one of a panel of such cell lines, wherein the panel can include different cell lines of the same type of disease and/or different cell lines of different diseases associated with expression of the genes of interest. Such a panel of cell lines can be useful, for example, to practice the present method when only a small number of cells can be obtained from the subject to be treated, thus providing a surrogate sample of the subject's cells, and also can be useful to include as control samples in practicing the present methods.

Once disease and/or skin lesion characterization is established and a treatment protocol is initiated, the methods of the invention may be repeated on a regular basis to monitor the expression profiles of the genes of interest in the subject. The results obtained from successive assays may be used to show the efficacy of treatment over a period ranging from several days to months. Accordingly, another aspect of the invention is directed to methods for monitoring a therapeutic regimen for treating a subject having skin cancer. A comparison of the expression profile or mutations in the nucleic acid sequence of the nucleic acid molecule prior to and during therapy will be indicative of the efficacy of the therapy. Therefore, one skilled in the art will be able to recognize and adjust the therapeutic approach as needed.

The efficacy of a therapeutic regimen for treating a cancer over time can be identified by an absence of symptoms or clinical signs of the particular cancer in a subject at the time of onset of therapy. In subjects diagnosed as having the particular cancer, the efficacy of a method of the invention can be evaluated by measuring a lessening in the severity of the signs or symptoms in the subject or by the occurrence of a surrogate end-point for the disorder.

In addition, such methods may help identify an individual as having a predisposition for the development of the disease, or may provide a means for detecting the disease prior to the appearance of actual clinical symptoms. A more definitive diagnosis of this type may allow health professionals to employ preventative measures or aggressive treatment earlier thereby preventing the development or further progression of the cancer.

When performed in a high throughput (or ultra-high throughput) format, the methods of the invention can be performed on a solid support (e.g., a microtiter plate, a silicon wafer, or a glass slide), wherein cell samples and/or genes of interest are positioned such that each is delineated from each other (e.g., in wells). Any number of samples or genes (e.g., 96, 1024, 10,000, 100,000, or more) can be examined in parallel using such a method, depending on the particular support used. Where samples are positioned in an array (i.e., a defined pattern), each sample in the array can be defined by its position (e.g., using an x-y axis), thus providing an “address” for each sample. An advantage of using an addressable array format is that the method can be automated, in whole or in part, such that cell samples, reagents, genes of interest, and the like, can be dispensed to (or removed from) specified positions at desired times, and samples (or aliquots) can be monitored, for example, for expression products and/or mutations in the nucleic acid sequence of the nucleic acid molecules from any one of the genes listed in Tables 1-8, 10-12, and 15.

Thus, the microarray can be used to monitor the expression level of large numbers of genes simultaneously (to produce a transcript image), and to identify genetic variants, mutations and polymorphisms. Polynucleotides used in the microarray may be oligonucleotides that are specific to a gene or genes of interest in which at least a fragment of the sequence is known or that are specific to one or more unidentified cDNAs which are common to a particular cell type, developmental or disease state. In order to produce oligonucleotides to a known sequence for a microarray, the gene of interest is examined using a computer algorithm which starts at the 5′ or more preferably at the 3′ end of the nucleotide sequence. The algorithm identifies oligomers of defined length that are unique to the gene, have a GC content within a range suitable for hybridization, and lack predicted secondary structure that may interfere with hybridization. In certain situations it may be appropriate to use pairs of oligonucleotides on a microarray. The “pairs” will be identical, except for one nucleotide which preferably is located in the center of the sequence. The second oligonucleotide in the pair (mismatched by one) serves as a control. The number of oligonucleotide pairs may range from two to one million. The oligomers are synthesized at designated areas on a substrate using a light-directed chemical process. The substrate may be paper, nylon or other type of membrane, filter, chip, glass slide or any other suitable solid support.

According to another aspect of the present invention, a kit is provided that is useful for detecting cancer in a cell or tissue, e.g., using the methods provided by the present invention for characterizing a skin lesion in a subject. In one embodiment, a kit of the invention includes a skin sample collection device and one or more probes or primers that selectively bind to one or more of the nucleic acid molecules in any of Tables 1-8, 10-12, and 15. In another embodiment, the kit includes one or more applicators in addition to or instead of the skin sample collection device. Such applicators are useful for in situ analysis of gene expression on the skin of a subject. For example, an applicator may be used to apply detectably labeled probes for visual detection of expressed RNA to characterize the skin lesion.

In another embodiment, a kit of the invention includes a probe that binds to a portion of a nucleic acid molecule in any of Tables 1-8, 10-12, and 15. In another embodiment, the kit further includes a microarray that contains at least a fragment of a gene or a nucleic acid molecule or a protein product of any one of the genes listed in Tables 1-8, 10-12, and 15. In some embodiments, many reagents may be provided in a kit of the invention, only some of which should be used together in a particular reaction or procedure. For example, multiple primers may be provided, only two of which are needed for a particular application.

In another embodiment, the kit of the invention provides a compartmentalized carrier including a first container containing a pair of primers. The primers are typically a forward primer that selectively binds upstream of a gene on one strand, and a reverse primer that selectively binds upstream of a gene on a complementary strand. Optionally the kits of the present invention can further include an instruction insert, e.g., disclosing methods for sample collection using the sample collection device and/or exemplary gene expression profiles for comparison with the expression profile of the sample taken from the subject.

The following examples are provided to further illustrate the advantages and features of the present invention, but are not intended to limit the scope of the invention. While they are typical of those that might be used, other procedures, methodologies, or techniques known to those skilled in the art may alternatively be used.

Example 1 RNA Quantitation and Profiling

The core hypothesis of this study is that epidermal cells overlying in situ or invasive melanoma, including but not limited to the stratum corneum, stratum lucidum, and stratum granulosum, can be recovered by adhesive means and that the quality and quantity of gene expression in the form of RNA contained within this sample is differently expressed than from a nearby epidermal sample, i.e. that the sampled RNA is diagnostic because of the underlying melanoma. It has been previously shown that changes in gene expression of specific genes are detectable in epidermal hyperplasia overlying cutaneous human melanoma samples obtained from surgical specimens of the epidermis (McCarty et al., 2003).

The present study is divided into two separate phases, a sample collection and characterization phase (phase 1) and an RNA profiling phase (phase 2). In phase 1 the tape stripped specimens and biopsied sample collections were performed by the principal investigator or trained individuals delegated by the principal investigator to obtain the biopsy sample at various sites. All biopsies are subject to standard histopathologic analysis. The RNA profiling phase (Phase 2), includes, but is not limited to RNA purification and hybridization to DNA microarrays for gene expression profiling.

Materials and reagents. Adhesive tape was purchased from Adhesives Research (Glen Rock, Pa.) in bulk rolls. These rolls were custom fabricated into small circular discs, 17 millimeters in diameter, by Diagnostic Laminations Engineering (Oceanside, Calif.). Human spleen total RNA was purchased from Ambion (catalogue #7970; Austin, Tex.). RNeasy RNA extraction kit was purchased from Qiagen (Valencia, Calif.). Reverse transcriptase, PCR primers and probes, and TaqMan Universal Master Mix, which included all buffers and enzymes necessary for the amplification and fluorescent detection of specific cDNAs, were purchased from Applied Biosystems (Foster City, Calif.). MELT total nucleic acid isolation system was purchased from Ambion (Austin, Tex.).

RNA isolation. RNA was extracted from tapes using either pressure cycling technology (PCT; Garrett, Tao et al. 2002; Schumacher, Manak et al. 2002) or MELT total nucleic acid system. Tapes were extracted in pairs by insertion into a PULSE™ tube (Pressure Biosciences, Gaithersburg, Md.) with 1.2 mls of buffer RLT (supplied in the Qiagen RNeasy kit). PULSE™ tubes were inserted into the PCT-NEP2017 pressure cycler and the sample was extracted using the following parameters: room temperature; 5 pressure cycles of 35 Kpsi with pressure held for 20 seconds at the top and bottom of each cycle. After pressure extraction the buffer was removed and used to process the remaining tapes used to strip that site; the buffer was then processed according to the standard Qiagen RNeasy protocol for the collection of larger RNAs (>200 nucleotides) by application to a purification column to which large RNA molecules (i.e. mRNAs) bind, while the column flow-through is saved for microRNA purification. The column flow-through, which contains miRNA separated from mRNA, is processed according to the Qiagen miRNA purification procedure (on the world wide web at qiagen.com/literature/protocols/pdf/RY20.pdf) to purify the microRNA. RNA from the 2 sites stripped on each subject was pooled to create a single sample from each subject.

RNA isolation using MELT total nucleic acid protocol. Tapes were extracted in a 2 ml eppendorf tube with 192 ml MELT buffer plus 8 ml of MELT cocktail and vortexed for 10 minutes at room temperature. The MELT lysates were transferred to the dispensed binding bead master mix after spinning down for 3 minutes at >10,000 xg and washed with 300 ml of Wash Solution 1 and 2. RNAs were eluted in 100 ml of elution solution.

Quantitation of mRNA. Experimental data is reported as the number of PCR cycles required to achieve a threshold fluorescence for a specific cDNA and is described as the “Ct” value (Gibson, Heid et al. 1996; Heid, Stevens et al. 1996; AppliedBiosystems 2001). Quantitation of total RNA mass was performed as previously described (Wong, Tran et al. 2004). Briefly, RNA mass recovered from tapes is determined by using quantitative RT-PCR with reference to a standard curve (Ct, actinvs. log[RNA]; AppliedBiosystems 2001) created from commercially purchased human spleen total RNA. The average of 6 replicate Ct, actin values was used to calculate the concentration of RNA in a sample with reference to the standard curve.

RNA amplification and array hybridization. RNA was isolated by the Multi-Enzymatic Liquefaction of Tissue method (Ambion, Austin, Tex.) and amplified using the WT-Ovation pico amplification system (NuGen, San Carlos, Calif.). The amplified RNA was hybridized to Affymetrix U133 plus 2.0 microarray and data were processed and analyzed using R from Bioconductor.

Sample size. Sample size calculations are presented in Example 2. This analysis predicts that in order to find 25-40 genes with high predictive value (p<0.001) for discriminating benign nevi from melanoma then approximately 30 melanomas and 30 non-melanoma lesions are needed.

Preprocessing GeneChip Data. The image files from scanning the Affymetrix GeneChips with the Affymetrix series 3000 scanner will be converted using GCOS software (Affymetrix) to “CEL” format files. Normalization of CEL files will be carried out using software from the Bioconductor suite (on the world wide web at bioconductor.org). In particular, a robust multiarray analysis with adjustments for optical noise and binding affinities of oligonucleotide probes (Wu et al., 2006; and Wu et al., 2004) as implemented by the function “just.gcrma” in the “gcrma” package will be used to normalize the GeneChip Data.

Statistical Approach for Microarray Data Analysis. Two generic statistical problems are addressed in this proposal: (i) identifying genes that are differentially expressed in different classes of lesions (i.e. melanoma versus non-melanoma lesions) and (ii) forming (and evaluating) rules for classification of melanoma and non-melanoma lesions into groups based on gene expression data.

The most important grouping divides melanoma from non-melanoma on the basis of biopsy results. The methods that will be used to address the problems identified above are now standard in the statistical evaluation of microarray data (for reviews see Smyth et al., 2003; and Lee, 2004)). These methods have been applied by others to data from Affymetrix arrays to study gene expression in prostate cancer (Stuart et al., 2004), to characterize changes in gene expression subsequent to HIV infection (Mitchell et al., 2003), and to develop a high throughput genotyping platform (Wolyn et al., 2004; and Borevitz et al., 2003). For identifying differentially expressed genes, permutation based estimates of false discovery rates (reviewed in Efron et al., 2002) are preferred. Scripts for the R quantitative programming environment were developed to implement these methods in our previous work, but will likely use or adapt the “siggenes” package from the Bioconductor suite in this project. The development of classification rules will rely on resampling methods (k-fold cross-validation, the 632 plus bootstrap, and/or bagging (Hastie et al., 2001) applied to the naive Bayes classifier and the nearest shrunken centroid classifier (Tibshirani et al., 2002) and the support vector machine (SVM) which both performed well in classifying prostate tissues as malignant or benign, used in our previous work. The implementation likely to be used is to perform k-fold cross-validation. Within each of the k train/test cycles an initial screen of the training data for differentially expressed genes is performed and genes are ordered according to their posterior probability of differential expression. Naive Bayes and nearest shrunken centroid classifiers based on the r genes with the highest posterior probability of differential expression are formed choosing enough values of r between 1 and 1024 to allow accurate interpolation of the classification error rate. The “one se rule” (Brieman et al., 1984) is applied to the error rates for the test sets to choose the classifier that minimizes the error rate. For SVM, an internal 632+ bootstrap is applied to each training sample to select the number of genes to be used in forming the classifier. The “1 se rule” error rates from the k test sets are used to characterize the classification accuracy.

In addition to the use of univariate and multivariate statistical analysis tools, sophisticated bioinformatic analysis approaches will help make sense of possible biological links between the genes found to be differentially expressed between, e.g., melanoma and non-melanoma samples. These approaches will focus on the analysis of genetic networks and pathways (Edelman et al., 2006; Kong et al., 2006; and Pang et al., 2006) and have been implemented in software packages such as Ingenuity (on the world wide web at ingenuity.com) and MetaCore (on the world wide web at genego.com). The identification of the biological links between genes that emerge from a gene expression microarray analysis can help put into context the biological meaningfulness of their expression patterns as well as help reduce the set of differentially expressed genes to be represented on a diagnostic panel based on their biology. The end result of this analysis will be to define a candidate expression classifier that will be validated in future, larger clinical trials.

QC metrics for RNA, amplified cDNA and microarray data. Following informed consent, the suspicious pigmented lesion was tape stripped using EGIR and then biopsied as per standard of care. The resulting RNA isolated from the EGIR tape was amplified and profiled on the Affymetrix U133 plus 2.0 GeneChip. Microarray data were normalized by the GCRMA algorithm. To assure high quality of microarray data are generated, QC metrics were established for RNA, amplified cDNA and microarray data. The quality of RNA was assessed by capillary electrophoresis using the Experion system (Biorad, Hercule, Calif.) and RNA with at least one visible 18S rRNA was further processed for RNA amplification. The amplified cDNA was quantified by the Nanodrop system and quality of the amplified cDNA was also assessed by the Experion system. The yield of the amplified cDNAs greater than 5 mg and the average size distribution of the cDNAs greater than 750 nt were carried forward for microarray hybridization. Quality of the array data was further assessed using simpleaffy program in R and the array data with scaling factor less than 5.0 and % present call greater than 30% were used for further data analysis.

Class Modeling—PAM. After passing the array data QC, 14 melanomas, 40 dysplastic nevi and 12 normal skin specimens were further analyzed. First, gene expression values less than 50 across all samples were filtered out and 16716 probesets were tested. These 16716 probesets were subjected to a statistical analysis for differentially expressed genes among melanomas, dysplastic nevi and normal skin using ANOVA (p<0.05), multiple testing correction algorithm (Westafall and Young permutation) and false discover rate (FDR) of 0.05. As indicated above, of the original 117 genes, an 89 gene panel (Table 2) was found to be a potential melanoma classifier. Further testing identified a 5-gene classifier (Table 3), a 30-gene classifier (Table 4) that includes newly identified genes, a 20-gene classifier (Table 5) that includes newly identified genes, and a 19-gene classifier that includes newly identified genes, which may all be used to discriminate melanomas from atypical nevi. The genes and respective classifier panels were analyzed using the Prediction Analysis of Microarrays (PAM) software freely available from Stanford University (Stanford, Calif.).

The PAM software uses a modification of the nearest centroid method, which computes a standardized centroid for each class in a training set. This refers to the average gene expression for each gene in each class divided by the within-class standard deviation for that gene. Nearest centroid classification takes the gene expression profile of a new sample, and compares it to each of these class centroids. The class, whose centroid it is closest to, in squared distance, is the predicted class for that new sample.

These genes were all subjected to a hierarchical clustering analysis and the melanoma specimens grouped together and were clearly distinguished from dysplastic nevi and normal skin. In addition, there are three distinct classes of dysplastic nevi; one is grouped together with normal skin and the second one was in between normal skin and melanomas, while the third one was grouped together with melanomas. These data suggest stratum corneum RNA, harvested by tape stripping with EGIR, can be used to distinguish melanoma from dysplastic nevi in suspiciously pigmented lesions.

The analysis of the genes as potential melanoma classifiers to discriminate between melanomas and dysplastic nevi was performed using t-test (p<0.01), FDR (0.05) and 2-fold difference between melanomas and dysplastic nevi. Of the original 117 genes, an 89 gene panel (Table 2) was found to be a potential melanoma classifier and functions of these 89 genes were subjected to Ingenuity Pathway Analysis (IPA) (Ingenuity, Redwood City, Calif.). Among them, 15 genes are involved hair and skin development and function, 18 genes are involved in cellular development, 16 genes are involved in cellular growth and proliferation and 24 genes are related to cancer. Thus, differentially expressed genes are genes related to biological functions in melanocytes including melanin biosynthesis, melanocyte proliferation, differentiation and development. (See FIGS. 5 and 6 ).

Class Modeling—Random Forests. Additional work, in which 31 melanomas, 71 atypical nevi, and 15 normal skin controls were analyzed by GeneChip assay, identified 284 differentially expressed genes (p<0.001, false discovery rate q<0.05). Hierarchical cluster analysis of these genes showed that melanomas can be distinguished from atypical nevi and normal skin, and, suggested the existence of different classes of atypical nevi (FIG. 7 ). Several of the genes were found by Ingenuity Pathways analysis to play a role in melanocyte development and function, as well as, skin development, cellular proliferation, and cancer. These findings further demonstrated that the presence of melanoma, directly or indirectly, alters the gene expression profile of stratum corneum. 229 genes were subject to Random Forests analysis and 61 of those 229 genes were found to discriminate melanoma from atypical nevi (see FIG. 8 ).

Random Forests analysis is based on Bagging Predictors, which is a method for generating multiple versions of a predictor and using these to get an aggregated predictor. The aggregation averages over the versions when predicting a numerical outcome and does a plurality vote when predicting a class. The multiple versions are formed by making bootstrap replicates of the learning set and using these as new learning sets. Tests on real and simulated data sets using classification and regression trees and subset selection in linear regression show that bagging can give substantial gains in accuracy. If perturbing the learning set can cause significant changes in the predictor constructed, then bagging can improve accuracy.

Class Modeling—TREENET®. 82 additional genes were identified (Table 7). TREENET® software (Salford Systems, San Diego, Calif.) was used to identify a 20-gene panel (Table 8), which may all be used to discriminate melanomas from atypical nevi (see FIG. 9 ). An additional 19-gene classifier was identified from 7199 differentially expressed genes between melanoma and nevi (Table 6; see also FIGS. 11 and 12 ). The 19-gene classifier was tested against independent samples and shown to be 100% sensitive and 88% specific for detection of melanomas. In addition, results from 10 melanomas and 10 nevi indicated that qRT-PCR recapitulated the data obtained using the GeneChip microarray (FIG. 12 and see raw data in Tables 13 and 14).

TREENET® is a data mining tool that is based on boosted decision trees. TREENET® is a model building and function approximation system that also serves as an initial data exploration tool. It can extract relationships in data and calibrate how predictable the outcomes will be, and can handle both classification and regression problems.

Example 2 Preliminary Power and Sample Size Studies Nevi vs. Primary Melanoma

The following sample size and power calculations are based exclusively on the large-scale cDNA study data provided in Haqq et al (2005). That data focused on normal skin (n=3 samples), nevi (n=9), primary melanomas (n=6) and metastatic melanomas (n=19). For purposes of the sample size calculations, the focus was on the comparison of nevi to primary melanomas. Power and sample size assessments were calculated based on the bootstrap strategy outlined by Page et al. Using the raw data available from the Haqq et al (2005) study, gene expression differences-based on all 14,772 probes used in their cDNA assay-between nevi and primary melanomas were computed using simple t-tests for each probe/gene. Note that multiple probes can be used interrogate individual genes. In addition, normal skin, nevi, and primary melanoma gene expression differences were also assessed in a three group analysis of variance (ANOVA), with the specific contrast between nevi and primary melanoma computed from this ANOVA. In the figures that follow, three main parameters are used to assess power and sample size. Table 9 (adapted from Page, et al.) shows the number of genes truly or not truly differentially expressed, and provides a simple way of describing these parameters, which are defined as follows (with the color of the curves corresponding to each parameter provided in parentheses for FIGS. 1A and 2A, although FIGS. 1B and 2B focus exclusively on the EDR as defined below.

EDR: Expected Discovery Rate (from Table 9, D/(B+D)). This reflects the expected proportion of probes/genes that will be declared significantly differentially expressed at the defined threshold (here taken to be, for the most part, p<0.05) that are, in fact, differentially expressed between nevi and primary melanomas.

PTP: Expected Proportion of probes/genes that are True Positives (Table 9, D/(C+D)). This proportion reflects the number of probes/genes showing expression differences that are likely to be truly differential expressed out of the total number of genes whose expression values result in test statistics less than the threshold (e.g., 0.05).

PTN: Probability of a True Negative result (Table 9, A/(A+B)). This probability concerns probes/genes that are not significantly different at the assumed threshold (e.g., 0.05) that are, in fact, not differentially expressed between skin and melanoma.

TABLE 9 Parameters of Relevance for Assessing the Power of Microarray Studies Not Truly Result based on differentially differentially array analysis expressed expressed Genes not significant A B Genes significant C D These columns represent the number of genes found to satisfy the given constraint; A = genes found not to be differentially expressed in an array experiment and that are truly not differentially expressed; B = genes that are differentially expressed but are not found to be differentially expressed in the array experiment (false negatives); C = genes that are found to be differentially expressed in the array experiment but are not truly differentially expressed (false positives); D = gene found to be differentially expressed in an array experiment and that are truly differentially expressed.

Nevi versus Primary data. The sample size analysis considered the number of samples necessary to “discover” or identify a probe or gene or set of probes/genes that could differentiate nevi from primary melanomas based on the probe/gene expression differences obtained by Haqq et al. (2005). FIG. 1 a provides a plot of the EDR, PTP, and PTN as a function of sample size, assuming a threshold for declaring the significance of a probe/gene expression difference between nevi and primary melanoma of p<0.05. Thus, from the plot, it appears that in order to “discover,” or identify, 80% of all genes that have been interrogated on a chip that exhibit a probe/gene expression difference producing a test statistic p-value <0.05 that will actually reflect a true probe/gene expression difference, a sample size of roughly 20 per nevi and primary melanoma group will be needed. Note that if all 14,772 probes are considered, one is likely to have 14,772×0.05=738 exhibit p-values <0.05 by chance alone, of which 1,727×0.80=1,381 will likely reflect true gene expression differences at that significance (i.e., p-value) level. If one is interested in identifying a smaller set of genes that have a greater probability of being detected as truly differentially expressed, a more stringent threshold for statistical significance (e.g., 0.001) can be used. This would generate 14,772×0.001=15 genes with p-values <0.001 by chance of which ˜45% (i.e., 34×0.45=7 would likely be truly differentially expressed at that level; see FIG. 1 b ; note curves in FIG. 1 b only correspond to the EDR with different assumed type I error rates).

A sample size analysis that considered the contrast results for nevi vs. primary melanoma in the context of an analysis of variance (ANOVA) comparing normal skin, nevi, and primary melanoma was also pursued. The rationale for this is that there are more differences between normal skin and either nevi or primary melanoma than there are between nevi and primary melanoma (based on an analysis of the Haqq et al (2005) data), and an analysis that considers normal skin gene expression variation may help reduce the noise in the assessment of nevi vs. primary melanoma gene expression differences. FIGS. 2 a and 2 b display the results of these analyses and provide similar sample size guidelines to those reflected in FIGS. 1 a and 1 b.

An analysis focusing exclusively on the posterior true probability (PTP) was also considered since, as discussed, there may be many probes/genes that exhibit differences between nevi and primary melanomas at a certain probability level purely by chance (given the large number of probes/genes interrogated). Thus, the likely fraction of these probes/genes that are truly differentially expressed is important to assess. FIGS. 3 a and 3 b reflect the results for different assumed significance levels.

Thus, an argument can be made that a study with approximately 20 samples per nevi and primary melanoma groups would have sufficient power to detect 80% of all genes that are likely to exhibit differential expression at a p-value level of 0.05 because they are, in fact, differentially expressed at this level. However, the number of genes (or probes) contributing to this set of differentially expressed genes is likely to number in the hundreds, if 10,000-30,000 probes are used or 5,000-10,000 genes are studied. If interest is in identifying a smaller number of probes or genes (˜25-40) that have a greater probability of being differentially expressed, say, at a p-value of 0.001, then ˜30 nevi and 30 primary melanoma samples would be needed (see FIGS. 1, 2, and 3 ).

Example 3 Tape Stripping to Recover Nucleic Acids from Normal Skin

The following procedure was used to recover nucleic acids from normal skin (e.g., the mastoid or upper back areas) of a subject.

Tapes were handled with gloved hands at all times. Locate a particular site that is relatively blemish-free and healthy, unless otherwise specified by the protocol. Preferred normal skin sites are the mastoid process (the bony process behind the ear at the base of the skull) and the upper back, immediately superior to the scapular spine. Shave the site if necessary to remove non-vellus hairs. Cleanse the site with an alcohol wipe (70% isopropyl alcohol). Let the site air dry completely before application of the tape. It is recommended to wait approximately 2 minutes to ensure the site is completely dry before application of the tape.

Apply the tape to the skin site. If more than one tape is used, apply tapes in sequential order starting from the left side. Use a surgical skin marker and/or a water soluble marker to mark the location of the tape on the skin in order to align subsequent tapes.

Start the tape harvesting procedure by applying pressure (press on the tape firmly). Ensure that the skin is held taut to ensure that the tape does not move while applying pressure. Then remove the tape slowly in one direction. Place the edge of the tape onto the strip at the top of the packet with the adhesive surface of the tape facing down to protect the sample. Put a second tape on the same site; apply pressure firmly as above. Remove the tape slowly in an opposite direction to that used in the immediately previous application.

Continue tape stripping by putting additional tapes on the same site, following the steps provided above. The site may stripped with a total of at least four tapes, unless otherwise specified in the protocol. Place the strip into a storage bag and immediately place the samples on dry ice or into storage at −20° C. or below until analysis.

Example 4 Tape Stripping to Recover Nucleic Acids from Pigmented Lesions

The following procedure was used to recover nucleic acids from pigmented lesions and/or skin suspected of melanoma of a subject. In contrast to normal skin, lesional skin should have a preoperative biopsy diameter of greater than or equal to about 6 mm, but less than that of the tape disc. Multiple lesions must be at least about 4 mm apart. The area of tape that touches the lesion should be generously demarcated on the tape with an insoluble ink pen so that this area may be cut away from the surrounding tape at the laboratory as part of the RNA extraction procedure.

As above, tapes were handled with gloved hands at all times. Shave the site if necessary to remove non-vellus hairs. Cleanse the site with an alcohol wipe (70% isopropyl alcohol). Let the site air dry completely before application of the tape. It is recommended to approximately 2 minutes to ensure the site is completely dry before application of the tape.

Apply the tape to the skin site. If more than one tape is used, apply tapes in sequential order starting from the left side. Use a surgical skin marker and/or a water soluble marker to mark the location of the tape on the skin in order to align subsequent tapes. Apply the tape to the suspect lesion, which should have a diameter that is greater than or equal to about 6 mm.

Start the tape harvesting procedure by applying pressure directly over the lesion and avoiding surrounding normal skin (press on the tape firmly). Ensure that the skin is held taut to ensure that the tape does not move while applying pressure. Using a marking pen, demarcate a zone around the lesion such that the area of the lesion is encompassed within the inked boundary and the boundary is approximately 1 mm from the lesion border.

Remove the tape slowly in one direction. Place the edge of the tape onto the adhesive strip with cells facing down to protect the sample. Put a second tape on the same site following directions provided above. Repeat until the lesion has been stripped a total of at least four times, unless otherwise specified in the protocol. Place the strip into a storage bag and immediately place the samples on dry ice or into storage at −20° C. or below until analysis.

Example 5 Gene Expression Profile to Distinguish Melanoma from Atypical Nevi

The purpose of this study is to determine whether stratum corneum RNA, harvested by tape stripping with EGIR can be used to distinguish melanoma from atypical nevi in suspicious pigmented lesions. See FIG. 4A.

Suspicious pigmented lesions were tape stripped four times using EGIR and then biopsied as per standard of care. Normal, uninvolved skin was tape stripped to serve as a negative control. All biopsies underwent primary and central review for histopathology. Total RNA was isolated from the tapes using MELT (Ambion, Inc.) and assessed for quality by Experion (Bio-Rad, Inc.) analysis. The yield of RNA was approximately 1 ng, as determined by quantitative RT-PCR of the specimen for p-actin gene expression. Total RNA (200-500 pg) was then amplified using the WT-Ovation Pico RNA Amplification System (NuGen, Inc.) and assayed for gene expression profile using the U133 plus 2.0 GeneChip (Affymetrix, Inc.).

The resulting RNA isolated from the EGIR tape is then amplified and profiled on the Affymetrix U133 plus 2.0 GeneChip. Microarray data is normalized by the GCRMA algorithm. Further analyses by means of ANOVA analysis (p<0.05) with a false discovery rate of 0.05 and multiple correction testing using Westfall and Young permutation identified approximately 117 genes as differentially expressed between melanoma, dysplastic nevi and normal skin (Table 1). Hierarchical clustering of these genes showed that the melanoma specimens grouped together and were clearly distinguished from dysplastic nevi and normal skin (FIG. 4B). In addition, 89 of the 117 genes shown in Table 1 were further identified (Table 2) as potential discriminators between melanoma and dysplastic nevi (p<0.01, false discovery rate q<0.05). When these 89 genes were subjected to Ingenuity Pathways analysis many were found to play roles in melanoma, hair and skin development and function, cellular development, cellular growth and proliferation and cancer. These findings demonstrate that EGIR-harvested RNA from suspicious pigmented skin lesions can be used to differentiate melanoma from dysplastic nevi (FIG. 4C). Further, these results suggest that the gene expression profile of stratum corneum is altered, either directly or indirectly, by the presence of melanoma (FIG. 4D).

In subsequent studies that compared normal and inflamed skin, sequential application of four small tapes at the same skin site recovered enough intact RNA to perform quantitative reverse-transcription polymerase chain reaction (qPCR) assay and DNA microarray analysis for investigation of gene expression. The latter assay was performed using the Affymetrix HG-U133A GeneChip following two rounds of amplification of 10 ng of total RNA sample that produced 30-80 pg of anti-sense RNA. Comparison of results from two subjects, each sampled at three separate sites, showed 12% intra- and inter-subject variance in gene measurements, a result that is well within the Affymetrix specified coefficient of variation (CV) for GeneChip assay. Of note is that differential expression of Y-chromosome genes was observed, a result that accurately distinguished the different genders of the 2 subjects. GeneChip assay was then performed on RNA isolated from tape stripping each of 3 subjects from normal, water occluded, and sodium lauryl sulfate-irritated study groups. The majority of 100 genes, whose expression is most significantly altered between untreated and SLS-treated skin showed, were already known to be involved in tissue inflammation and injury functions. Thus, RNA harvested by EGIR technology is more than adequate for microarray-based gene expression profiling and appropriately reflects the pathologic state of skin.

Recent work by Benson et al (2006) demonstrates that RNA can be recovered from psoriatic lesions and that the general RNA expression profile of tape strip recovered RNA is consistent with biopsy RNA derived from lesions on the same patient. Further work (see U.S. Pat. No. 7,183,057, incorporated herein by reference) has shown that psoriatic lesions can be sampled with tape during treatment with Enbrel and that strong correlations could be made between gene expression in week one of treatment and clinical response at weeks 4 and 8. This work further establishes the credentials of tape stripping for the recovery of physiologically relevant RNA from the surface of the skin.

Example 6 Gene Expression Profile to Distinguish Solar Lintigenes from Melanoma, Atypical Nevi, and/or Normal Skin

The purpose of this study is to determine whether stratum corneum RNA, can be used to distinguish solar lentigines from melanoma, atypical nevi, and/or normal skin in suspicious pigmented lesions.

Suspicious pigmented lesions were tape stripped as above and then biopsied as per standard of care. Normal, uninvolved skin was tape stripped to serve as a negative control. All biopsies underwent primary and central review for histopathology. Total RNA was isolated provided above and then amplified and profiled, as provided above. 1600 genes that were differentially expressed among solar lentigines and normal skin controls were selected. Further testing identified a 103-gene classifier (Table 10), which may be used to discriminate solar lentigines from normal pigmented skin (FIGS. 14 to 16 ).

Additional work, in which 11 solar lentigo samples, 12 atypical nevi samples, and 8 basal cell carcinoma (BCC) samples were analyzed using ANOVA (p<0.05), FDR (p<0.05) and multiple test correction to identify 82 differentially expressed genes (Table 11). Heirarchical analysis of the 82-gene classifier shows that it may be used to discriminate between solar lentigines and atypical nevi and/or basal cell carcinoma (BCC) (FIG. 17 ). Finally, a 32-gene classifier (Table 12) was identified, which may be used to discriminate between solar lentigines and lentigo maligna (FIG. 18 ). The genes and respective classifier panels were analyzed using the Prediction Analysis of Microarrays (PAM) software freely available from Stanford University (Stanford, Calif.).

An additional 28-gene classifier was identified from 2437 differentially expressed genes between lentigo maligna and solar lentigo was identified by TREENET® analysis (Table 15; see also FIG. 19 ). In addition, results from 26 lentigo maligna and 34 solar lentigo samples indicated that qRT-PCR recaptilated data obtained using the GeneChip microarray (see raw data in Tables 16-21).

REFERENCES

-   Jemal A, Murray T, Samuels A, Ghafoor A, Ward E, Thun M J: Cancer     statistics, 2003. CA Cancer J Clin 2003, 53(1):5-26. -   Gloster H M, Jr., Brodland D G: The epidemiology of skin cancer.     Dermatol Surg 1996, 22(3):217-226. -   Albert V A, Koh H K, Geller A C, Miller D R, Prout M N, Lew R A:     Years of potential life lost: another indicator of the impact of     cutaneous malignant melanoma on society. JAm Acad Dermatol 1990,     23(2 Pt 1):308-310. -   Morhenn V B, Chang E Y, Rheins L A: A noninvasive method for     quantifying and distinguishing inflammatory skin reactions. J Am     Acad Dermatol 1999, 41(5 Pt 1):687-692. -   Wong R, Tran V, Morhenn V, Hung S P, Andersen B, Ito E, Wesley     Hatfield G, Benson N R: Use of RT-PCR and DNA microarrays to     characterize RNA recovered by non-invasive tape harvesting of normal     and inflamed skin. J Invest Dermatol 2004, 123(1):159-167. -   Benson N R, Papenfuss J, Wong R, Motaal A, Tran V, Panko J, Krueger     G G: An analysis of select pathogenic messages in lesional and     non-lesional skin using non-invasive tape harvesting. Journal of     Investigative Dermatology 2006, 126(10):2234-2241. -   Baldi A, Santini D, De Luca A, Paggi M G: cDNA array technology in     melanoma: an overview. J Cell Physiol 2003, 196(2):219-223. -   Carr K M, Bittner M, Trent J M: Gene-expression profiling in human     cutaneous melanoma. Oncogene 2003, 22(20):3076-3080. -   Gershenwald J E, Bar-Eli M: Gene expression profiling of human     cutaneous melanoma: are we there yet? Cancer Biol Ther 2004,     3(1):121-123. -   Kim C J, Reintgen D S, Yeatman T J: The promise of microarray     technology in melanoma care. Cancer Control 2002, 9(1):49-53. -   Seftor R E, Seftor E A, Koshikawa N, Meltzer P S, Gardner L M,     Bilban M, Stetler-Stevenson W G, Quaranta V, Hendrix M J:     Cooperative interactions of laminin 5 gamma2 chain, matrix     metalloproteinase-2, and membrane type-1-matrix/metalloproteinase     are required for mimicry of embryonic vasculogenesis by aggressive     melanoma. Cancer Res 2001, 61(17):6322-6327. -   Su Y A, Bittner M L, Chen Y, Tao L, Jiang Y, Zhang Y, Stephan D A,     Trent J M: Identification of tumor-suppressor genes using human     melanoma cell lines UACC903, UACC903(+6), and SRS3 by comparison of     expression profiles. Mol Carcinog 2000, 28(2):119-127. -   Haqq C, Nosrati M, Sudilovsky D, Crothers J, Khodabakhsh D, Pulliam     B L, Federman S, Miller J R, 3rd, Allen R E, Singer M I et al: The     gene expression signatures of melanoma progression. Proc Natl Acad     Sci USA 2005, 102(17):6092-6097. -   Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner F L,     Walker M G, Watson D, Park T et al: A multigene assay to predict     recurrence of tamoxifen-treated, node-negative breast cancer. N Engl     J Med 2004, 351(27):2817-2826. -   Pavey S, Johansson P, Packer L, Taylor J, Stark M, Pollock P M,     Walker G J, Boyle G M, Harper U, Cozzi S J et al: Microarray     expression profiling in melanoma reveals a BRAF mutation signature.     Oncogene 2004, 23(23):4060-4067. -   McCarty M F, Bielenberg D R, Nilsson M B, Gershenwald J E, Barnhill     R L, Ahearne P, Bucana C D, Fidler I J: Epidermal hyperplasia     overlying human melanoma correlates with tumour depth and     angiogenesis. Melanoma Res 2003, 13(4): 379-387. -   Stolz W, Schmoeckel C, Welkovich B, Braun-Falco O: Semiquantitative     analysis of histologic criteria in thin malignant melanomas. J Am     Acad Dermatol 1989, 20(6): 1115-1120. -   Wu Z, Irizarry R A: Stochastic models inspired by hybridization     theory for short oligonucleotide arrays. J Comput Biol 2005,     12(6):882-893. -   Wu Z, Irizarry R A: Preprocessing of oligonucleotide array data. Nat     Biotechnol 2004, 22(6):656-658; author reply 658. -   Smyth G K, Yang Y H, Speed T: Statistical issues in cDNA microarray     data analysis. Methods Mol Biol 2003, 224:111-136. -   Lee M-LT: Analysis of microarray gene expression data. Boston:     Kluwer Academic Publishers; 2004. -   Stuart R O, Wachsman W, Berry C C, Wang-Rodriguez J, Wasserman L,     Klacansky I, Masys D, Arden K, Goodison S, McClelland M et al: In     silico dissection of cell-type-associated patterns of gene     expression in prostate cancer. Proc Natl Acad Sci USA 2004,     101(2):615-620. -   Mitchell R, Chiang C Y, Berry C, Bushman F: Global analysis of     cellular transcription following infection with an HIV-based vector.     Mol Ther 2003, 8(4):674-687. -   Wolyn D J, Borevitz J O, Loudet O, Schwartz C, Maloof J, Ecker J R,     Berry C C, Chory J: Light-response quantitative trait loci     identified with composite interval and eXtreme array mapping in     Arabidopsis thaliana. Genetics 2004, 167(2):907-917. -   Borevitz J O, Liang D, Plouffe D, Chang H S, Zhu T, Weigel D, Berry     C C, Winzeler E, Chory J: Large-scale identification of     single-feature polymorphisms in complex genomes. Genome Res 2003,     13(3):513-523. -   Efron B, Tibshirani R: Empirical bayes methods and false discovery     rates for microarrays. Genet Epidemiol 2002, 23(1):70-86. -   Hastie T, Tibshirani R, Friedman J: The elements of statistical     learning: Date mining, inference, and prediction. New York:     Springer-Verlag; 2001. -   Tibshirani R, Hastie T, Narasimhan B, Chu G: Diagnosis of multiple     cancer types by shrunken centroids of gene expression. Proc Natl     Acad Sci USA 2002, 99(10):6567-6572. -   Brieman L, Friedman J, Olshen R, Stone C: Classification and     regression trees. Belmont, Calif.: Wadsworth International Group;     1984. -   Edelman E, Porrello A, Guinney J, Balakumaran B, Bild A, Febbo P G,     Mukherjee S: Analysis of sample set enrichment scores: assaying the     enrichment of sets of genes for individual samples in genome-wide     expression profiles. Bioinformatics 2006, 22(14):e108-116. -   Kong S W, Pu W T, Park P J: A multivariate approach for integrating     genome-wide expression data and biological knowledge. Bioinformatics     2006. -   Pang H, Lin A, Holford M, Enerson B E, Lu B, Lawton M P, Floyd E,     Zhao H: Pathway analysis using random forests classification and     regression. Bioinformatics 2006, 22(16):2028-2036. -   Page G P, Edwards J W, Gadbury G L, Yelisetti P, Wang J, Trivedi P,     Allison D B: The PowerAtlas: a power and sample size atlas for     microarray experimental design and research. BMC Bioinformatics     2006, 7:84.

TABLE 1 Entrez Entrez Entrez Gene ID Gene ID Gene for for ID name matched term synonym description Human Mouse for Rat ACTR1B 202135_s_at 2310066K23Rik, ARP1 actin-related 10120 226977 (includes AA960180, protein 1 homolog B, EG:10120) ACTR1B, centractin beta (yeast) AI851923, ARP1B, CTRN2, MGC36526 ANGEL1 213099_at 1110030H02Rik, angel homolog 1 23357 68737 362765 KIAA0759, (Drosophila) mKIAA0759, RGD1306238 ANKRD13B 227720_at AW124583, ankyrin repeat domain 124930 268445 360575 B930093C12Rik, 13B FLJ20418, FLJ25555, RGD1564005 ANKRD44 228471_at 4930444A19Rik, ankyrin repeat domain 44 91526 329154 301415 A130096K20, E130014H08Rik, LOC91526, MGC21968, MGC70444, RGD1561893 ARHGEF19 226857_at 6030432F23, Rho guanine nucleotide 128272 213649 362648 6430573B13Rik, exchange factor (GEF) 19 FLJ33962, RP4- 733M16.1, WGEF ATPBD4 238662_at 5730421E18Rik, ATP binding domain 4 89978 66632 362191 MGC14798, RGD1310006 BARX2 210419_at 2310006E12Rik, BarH-like homeobox 2 8538 12023 Barx2b, MGC133368, MGC133369 BDNF 206382_s_at MGC105254, brain-derived 627 12064 24225 MGC34632 neurotrophic factor BLOC1S1 202592_at AI839753, biogenesis of lysosome- 2647 14533 288785 BLOC-1 subunit 1, related organelles BLOS1, GCN5-like complex-1, subunit 1 protein 1, GCN5L1, MGC87455, RT14 BTG2 201236_s_at AA959598, Agl, BTG family, member 2 7832 12227 29619 An, an-1, APRO1, MGC126063, MGC126064, PC3, TIS21 C16ORF48 223407_at AI606951, chromosome 16 open 84080 102124 291975 DAKV6410, reading frame 48 DKFZP434A1319, E130303B06Rik, RGD1307357 C6ORF218 244829_at MGC40222 chromosome 6 open 221718 reading frame 218 C8ORF13 233641_s_at A030013D21, chromosome 8 open 83648 219148 498533 BC065085, reading frame 13 D8S265, DKFZp761G151, MGC120649, MGC120650, MGC120651, RGD1561302 CCDC95 227286_at AI225782, coiled-coil domain 283899 233875 AI854876, Ccdc85, containing 95 FLJ00079, FLJ90652, MGC31515 CCHCR1 37425_g_at C6orf18, HCR, coiled-coil alpha-helical 54535 240084 406196 MGC126371, rod protein 1 MGC126372, MGC28303, RGD:1302992, SBP CIRBP 230142_s_at A18 HNRNP, cold inducible RNA 1153 12696 81825 CIRP, R74941 binding protein CLSTN2 219414_at 2900042C18Rik, calsyntenin 2 64084 64085 171394 AI448973, alcagamma, CS2, Cst-2, CSTN2, FLJ39113, FLJ39499, KIAA4134, MGC119560, mKIAA4134 COL7A1 217312_s_at AW209154, collagen, type VII, alpha 1 1294 12836 301012 EBD1, EBDCT, (epidermolysis bullosa, EBR1 dystrophic, dominant and recessive) DACH1 205471_s_at, AI182278, Dac, dachshund homolog 1 1602 13134 205472_s_at, DACH, (Drosophila) 228915_at E130112M23Rik, FLJ10138 DCT 205337_at, DT, RGD1564975, dopachrome tautomerase 1638 13190 290484 205338_s_at slaty, slt, TRP-2, (dopachrome delta- TYRP2 isomerase, tyrosine-related protein 2) DOCK10 219279_at 9330153B10RIK, dedicator of cytokinesis 55619 210293 301556 A630054M16Rik, 10 DKFZp781A1532, DRIP2, Jr4, Jr5, mKIAA0694, Nbla10300, R75174, RGD1561963, ZIZ3, Zizimin3 DRAP1 1556181_at 2310074H19Rik, DR1-associated protein 1 10589 66556 293674 MGC156767, (negative cofactor 2 alpha) NC2-ALPHA, negative cofactor 2 alpha EDNRB 204271_s_at, ABCDS, endothelin receptor type 1910 13618 50672 206701_x_at AU022549, B Ednra, ET&gt;B&lt, ET-B, ETB RECEPTOR, ETBR, ETRB, GUSB, HSCR, HSCR2, Sox10m1 EFNA4 205107_s_at EFL-4, EPHRIN ephrin-A4 1945 13639 310643 A4, Epl4, EPLG4, LERK-4, MGC125826 EHD2 45297_at BC027084, EH-domain containing 2 30846 259300 361512 C130052H20Rik, MGC25606, MGC38650, MGEPS, PAST2 ETS1 224833_at AI196000, v-ets erythroblastosis 2113 23871 24356 AI448617, C-ETS1, virus E26 oncogene D230050P06, homolog 1 (avian) Etsoncb, EWSR2, FLJ10768, MGC124638, MGC130355, MGC18571, p42 ETS1, p51 ETS1, Tp11 FAM33A 225684_at 1110001A07Rik, family with sequence 348235 66140| 287598 C78640, similarity 33, member A 625534 EG625534, FLJ12758, MGC109093, MGC110975, MGC151378, RGD1307084 FGFR1 210973_s_at, AW208770, fibroblast growth factor 2260 14182 79114 211535_s_at BFGFR, C-FGR, receptor 1 (fms-related CD331, CEK, tyrosine kinase 2, Pfeiffer FGF1 syndrome) RECEPTOR, FGFBR, FGFR1- IIIC, Fgfr1c, FLG, Flk2, FLT2, H5, HBGFR, KAL2, N-SAM FOXO1A 202723_s_at Afxh, AI876417, forkhead box O1A 2308 56458 84482 FKH1, FKHR, (rhabdomyosarcoma) FKHR1, Forkhead, FOXO1 FOXP1 223936_s_at 12CC4, forkhead box P1 27086 108655 297480 3110052D19Rik, 4932443N09Rik, AI461938, AW494214, FLJ23741, hFKH1B, HSPC215, MGC116362, MGC12942, MGC88572, MGC99551, QRF1 FRAT2 209864_at MGC10562, frequently rearranged in 23401 212398 MGC37615 advanced T-cell lymphomas 2 GCLM 203925_at Gamma gclm, glutamate-cysteine ligase, 2730 14630 29739 Gamma modifier subunit glutamylcysteine synthase (regulatory), GAMMA GLUTAMYLCY STEINE SYNTHETASE, Gcs Ls, Gcs, Regulatory, GCS- L, GCS1, Gcslc, GLCLR, glutamat-cystein ligase, regulatory subunit GGA3 209411_s_at C230037M19Rik, golgi associated, gamma 23163 260302 360658 KIAA0154, adaptin ear containing, mKIAA0154 ARF binding protein 3 GLUL 200648_s_at GLNS, glutamate-ammonia 2752 14645 Glutamine ligase (glutamine Synthase, synthetase) GLUTAMINE SYNTHETASE, GS, MGC128403, PIG43 GPR161 214104_at FLJ33952, G- G protein-coupled 23432 240888 289180 protein coupled receptor 161 receptor aft091890, Gm208, Gm208Gpr, RE2, RGD1563245 HEY2 219743_at CHF1, GRL, hairy/enhancer-of-split 23493 15214 155430 HERP1, HESR2, related with YRPW motif HRT2, MGC10720 2 HIST2H2AA3 214290_s_at AI448581, H2A, histone cluster 2, H2aa3 8337 15267 365877 H2a-615, H2A.2, H2A/O, H2A/q, H2AFO, Hist2, HIST2H2AA, Hist2h2aa1 ID1 208937_s_at AI323524, inhibitor of DNA binding 3397 15901 25261 D2Wsu140e, ID, 1, dominant negative ID-1H, ID125A, helix-loop-helix protein Idb1, MGC156482 KALRN 227750_at 2210407G14Rik, kalirin, RhoGEF kinase 8997 545156 84009 AV235988, DUET, Duo, E530005C20Rik, FLJ16443, Gm539, HAPIP, KALIRIN, Kalirin7, Pcip10, TRAD KDELR1 200922_at 8030486F04Rik, KDEL (Lys-Asp-Glu- 10945 68137 361577 AW215843, Leu) endoplasmic ERD2, ERD2.1, reticulum protein retention HDEL, KDEL receptor 1 RECEPTOR, Kdelr, MGC109169, PM23 KIAA0738 210529_s_at 2810407D09Rik, KIAA0738 gene product 9747 77574 362353 3321401G04Rik, A230020K05Rik, AI848529, RGD1565474 KIT 205051_s_at Bs, C-KIT, c-Kit v-kit Hardy-Zuckerman 4 3815 16590 64030 Gnnk+, CD117, feline sarcoma viral Fdc, SCFR, Ssm, oncogene homolog Tr Kit, white- spotted LGR4 230674_at 9130225G07, leucine-rich repeat- 55366 107515 286994 A930009A08Rik, containing G protein- GPCR48, GPR48 coupled receptor 4 LHX2 211219_s_at ap, apterous, LIM homeobox 2 9355 16870 296706 (includes hLhx2, Lh-2, EG:9355) LH2A, Lhx2, Lim2, MGC138390 LMO4 209204_at A730077C12Rik, LIM domain only 4 8543 16911 362051 Crp3, Etohi4, MGC105593 LOC254100 1557131_at hypothetical protein 254100 LOC254100 LRIG1 236173_s_at, D6Bwg0781e, leucine-rich repeats and 26018 16206 312574 238339_x_at DKFZP586O1624, immunoglobulin-like Img, LIG-1 domains 1 MED28 222635_s_at 1500003D12Rik, mediator of RNA 80306 66999 305391 AI451633, polymerase II AU045690, transcription, subunit 28 DKFZP434N185, homolog (S. cerevisiae) EG1, FKSG20, magicin, RGD1305875 MKL1 215292_s_at AI852829, megakaryoblastic 57591 223701 315151 AMKL, leukemia (translocation) 1 AW743281, AW821984, BSAC, MAL, MRTF-A MLANA 206426_at, A930034P04Rik, melan-A 2315 77836 293890 206427_s_at MART-1, MELAN-A, MGC130556 MLLT6 225628_s_at AF17, myeloid/lymphoid or 4302 246198 303504 AI315037, mixed-lineage leukemia FLJ23480 (trithorax homolog, Drosophila); translocated to, 6 MLPH 218211_s_at 2210418F23Rik, melanophilin 79083 171531 316620 5031433109Rik, AW228792, D1Wsu84e, l(1)- 3Rk, 11Rk3, ln, MGC2771, MGC59733, SLAC2-A MYEF2 222771_s_at, 9430071B01, myelin expression factor 50804 17876 362207 232676_x_at FLJ11213, 2 HsT18564, KIAA1341, MEF-2, MGC109392, MGC87325, mKIAA1341, MST156, MSTP156 MYL6B 204173_at 5730437E04Rik, myosin, light chain 6B, 140465 216459 317454 Atrial Myosin alkali, smooth muscle and Light Chain 1, non-muscle BC037527, MGC41229, MLC1SA, RGD1560334 MYO5A 227761_at 9630007J19Rik, myosin VA (heavy chain 4644 17918 25017 AI413174, 12, myoxin) AI661011, Br Myosin5a, d- 120J, Dbv, Dop, flail, flr, GS1, hcBM-V, MVa, MYH12, MYO5, myosin V, MYOSIN VA, MYOSIN VA EXON CONTAINING, MYOVA, MYOXIN, MYR12, Sev-1 NBL1 37005_at D1S1733E, neuroblastoma, 4681 17965 50594 D4H1S1733E, suppression of DAN, Dana, tumorigenicity 1 DAND1, MGC123430, MGC8972, NB, NO3 NFIB 230791_at 6720429L07Rik, nuclear factor I/B 4781 18028 29227 CTF/NF1B, E030026I10Rik, NF1-B, NFI- RED, NFIB2, NFIB3, Nuclear factor 1/B OSTM1 218196_at 1200002H13Rik, osteopetrosis associated 28962 14628 445370 AW123348, transmembrane protein 1 GIPN, GL, HSPC019 PDK3 221957_at 2610001M10Rik, pyruvate dehydrogenase 5165 236900 296849 AI035637, kinase, isozyme 3 MGC6383 PKD1 241090_at FLJ00285, polycystic kidney disease 5310 18763 24650 mFLJ00285, 1 (autosomal dominant) MGC118471, PBP, PC-1, POLYCYSTIN1 PLEKHA5 220952_s_at 2810431N21Rik, pleckstrin homology 54477 109135 246237 AI428202, domain containing, family AK129423, A member 5 Ayu21-9, FLJ10667, FLJ31492, Gt(pU21)9Imeg, Image:3710928, KIAA1686, MGC38455, PEPP2, TRS1 PLP1 210198_s_at DM20, jimpy, jp, proteolipid protein 1 5354 18823 24943 MMPL, Msd, (Pelizaeus-Merzbacher PLP, PLP/DM20, disease, spastic paraplegia PMD, 2, uncomplicated) PROTEOLIPID, RSH, SPG2 PLXNC1 213241_at 2510048K12Rik, plexin C1 10154 54712 362873 AW742158, CD232, Plexin C1, VESPR PPP3CA 202425_x_at 2900074D19Rik, protein phosphatase 3 5530 19055 24674 AI841391, (formerly 2B), catalytic AW413465, subunit, alpha isoform Calcineurin, (calcineurin A alpha) Calcineurin A Alpha, CALN, CALNA, CALNA1, CCN1, CN, CnA, CnA- alpha, CNA1, MGC106804, Pp2b Subunit A, PPP2B PRKCSH 200707_at 80K-H, AGE-R2, protein kinase C substrate 5589 19089 300445 G19P1, PCLD, 80K-H PLD, PLD1 PRKD3 222565_s_at 4930557O20Rik, protein kinase D3 23683 75292 313834 5730497N19Rik, EPK2, MGC47171, nPKC-NU, PKC- NU, PKD3, PRKCN PRMT1 206445_s_at 6720434D09Rik, protein arginine 3276 15469 60421 ANM1, methyltransferase 1 AW214366, HCP1, heterogeneous ribonucleooproteins methyltransferase- like 2, Hnmt112, Hramt, HRMT1L2, IR1B4, Mrmt1 PSCD3 225147_at AI648983, pleckstrin homology, 9265 19159 116693 ARNO3, Sec7 and coiled-coil CYTOHESIN-3, domains 3 GRP1, KIAA4241, MGC124579, mKIAA4241, Sec7, Sec7C PTPRF 200635_s_at, AA591035, protein tyrosine 5792 19268 360406 200637_s_at FLJ43335, phosphatase, receptor FLJ45062, type, F FLJ45567, LAR, Lar ptp2b, LARFN5C, LARS PTPRM 1555579_s_at HR-PTPU, protein tyrosine 5797 19274 29616 KIAA4044, phosphatase, receptor MGC90724, type, M mKIAA4044, PTP-MU, PTPRL1, R-PTP- MU, RPTPM, RPTPU PVRL1 225211_at AI835281, poliovirus receptor- 5818 58235 192183 AW549174, related 1 (herpesvirus CD111, entry mediator C; nectin) CLPED1, ED4, HIgR, HVEC, MGC142031, MGC16207, NECTIN-1, Nectin1 alpha, Nectin1 delta, OFC7, PRR, PRR1, PVRR, PVRR1, SK-12 RAB40C 227269_s_at RAB40, RAR3, RAB40C, member RAS 57799 224624 359728 RARL, RASL8C oncogene family RASSF3 230466_s_at AW212023, Ras association 283349 192678 362886 AW322379, (RalGDS/AF-6) domain MGC119194, family 3 MGC119195, MGC119197, RASSF5 RHOQ 212120_at ARHQ, ras homolog gene family, 23433 104215 85428 RASL7A, Rhot, member Q TC10, TC10 BETA, TC10A SAT1 203455_s_at, AA617398, spermidine/spermine N1- 6303 20229 302642 210592_s_at, Ab2-402, DC21, acetyltransferase 1 213988_s_at, KFSD, MGC72945, 230333_at SAT, Spermidine/ spermine N1-acetyl transferase, SSAT, SSAT-1 SDCBP 200958_s_at MDA-9, ST1, syndecan binding protein 6386 53378 83841 SYCL, (syntenin) SYNTENIN, Syntenin-1, TACIP18 SEC61A1 217716_s_at, AA408394, Sec61 alpha 1 subunit 29927 53421 80843 222385_x_at AA410007, (S. cerevisiae) HSEC61, rSEC61alpha p, SEC61, Sec61 alpha, SEC61 ALPHA1, SEC61A SEMA3C 236947_at 1110036B02Rik, sema domain, 10512 20348 296787 SEMAE, immunoglobulin domain SEMAPHORINE, (Ig), short basic domain, SemE secreted, (semaphorin) 3C SERGEF 220482_s_at, DELGEF, Gef, secretion regulating 26297 27414 365243 232983_s_at Gnef, Gnefr, guanine nucleotide MGC141208, exchange factor MGC141209, RGD1563497 SILV 209848_s_at D10H12S53E, silver homolog (mouse) 6490 20431 362818 D12S53E, D12S53Eh, GP100, gp87, ME20, PMEL17, SI, SIL SLC2A4RG 227362_at GEF, HDBP1, SLC2A4 regulator 56731 Si-1-2, Si-1-2-19 SLC7A1 212295_s_at 4831426K01Rik, solute carrier family 7 6541 11987 25648 AI447493, (cationic amino acid ATRC1, CAT-1, transporter, y+ system), EcoR, ER, ERR, member 1 HCAT1, mCAT-1, Rec-1, REC1L, REV-1 SRGAP2 1568957_x_at 9930124L22Rik, SLIT-ROBO Rho 23380 14270 360840 AI448945, FBP2, GTPase activating protein FNBP2, 2 KIAA0456, RGD1566016, srGAP3 SSBP3 217991_x_at, 2610021L12Rik, single stranded DNA 23648 72475 84354 223635_s_at 2610200M23Rik, binding protein 3 5730488C10Rik, AI854733, AW551939, CSDP, FLJ10355, LAST, MGC124589, SSDP, SSDP1, Ssdp3 STAM 203544_s_at DKFZp686J2352, signal transducing 8027 20844 498798 (includes RGD1564499, adaptor molecule (SH3 EG:8027) Stam, STAM1 domain and ITAM motif) 1 SYNGR2 201079_at CELLUGYRIN, synaptogyrin 2 9144 20973 89815 Clast2, MGC102914 TCF7L2 212759_s_at mTcf-4B, mTcf- transcription factor 7-like 6934 21416 (includes 4E, TCF-4, 2 (T-cell specific, HMG- EG:6934) TCF4B, TCF4E, box) Tcf712 TIMM17A 215171_s_at 17kDa, translocase of inner 10440 21854 54311 Mitochondrial mitochondrial membrane import inner 17 homolog A (yeast) membrane translocase, Mitochondrial protein import protein 2, mTim17a, TIM17, TIM17A, Timm17 TP53 201746_at bbl, bfy, bhy, tumor protein p53 (Li- 7157 22059 24842 Delta N p53, LFS1, Fraumeni syndrome) MGC112612, P53, TRP53 TP53INP1 235602_at 2700057G22Rik, tumor protein p53 94241 60599 297822 DKFZP434M131 inducible nuclear protein 1 7, FLJ22139, p53DINP1, SIP, SIP18, SIP27, Stinp, Teap, Thymus Expressed Acidic Protein, TP53DINP1, TP53DINP1alpha, TP53INP1A, TP53INP1B, Trp53inp1 TRIB2 202478_at AW319517, tribbles homolog 2 28951 217410 313974 C5fw, GS3955, (Drosophila) RGD1564451, TRB-2 TRPM1 237070_at 4732499L03Rik, transient receptor 4308 17364 (includes AI606771, potential cation channel, EG:4308) LTRPC1, subfamily M, member 1 melastatin, MLSN, MLSN1, Trpm1 TSPAN6 209108_at 6720473L21Rik, tetraspanin 6 7105 56496 302313 AI316786, MGC117923, T245, Tm4sf, TM4SF6 TSTA3 36936_at AI256181, FX, tissue specific 7264 22122 300036 FX protein, transplantation antigen MGC113801, P35B P35B, Tstap35b TTC3 208073_x_at, 2610202A04Rik, tetratricopeptide repeat 7267 22129 360702 210645_s_at AA409221, domain 3 D16Ium21, D16Ium21e, DCRR1, DKFZp686M0150, KIAA4119, mKIAA4119, Mtprd, RNF105, TPRD, TPRDIII TUBB4 212664_at AI325297, Beta tubulin, beta 4 10382 22153 29213 tubulin, BETA TUBULIN 4 ALPHA, Beta tubulin class iv, beta-5, Beta4 Tubulin, M(beta)4, Tubb, TUBB5, TUBULIN BETA (5-BETA), TUBULIN BETA5 TYR 206630_at albino, Dopa tyrosinase 7299 22173 308800 oxidase, (oculocutaneous albinism Melanogenesis IA) Related Tyrosinase, OCA1A, OCAIA, skc35, Tyr&lt; c-em&gt;, TYROSINASE TYRP1 205694_at b-PROTEIN, tyrosinase-related protein 7306 22178 298182 brown, CAS2, 1 CATB, GP75, isa, MELANOMA ANTIGEN GP75, TRP, TRP-1, TYRP VDR 204255_s_at NR1I1, VD3R, vitamin D (1,25- 7421 22337 24873 VITAMIN D dihydroxyvitamin D3) RECEPTOR receptor VGLL4 214004_s_at BC048841, vestigial like 4 9686 232334 297523 KIAA0121, (Drosophila) MGC109514, MGC54805, VGL-4 YIPF5 224949_at 2610311I19Rik, Yip1 domain family, 81555 67180 361315 AA408236, member 5 Ac2-256, DKFZp313L2216, FinGER5, SB140, SMAP-5, YIP1A ZFHX1B 1557797_a_at, 9130203F04Rik, zinc finger homeobox 1b 9839 24136 311071 203603_s_at D130016B08Rik, KIAA0569, mKIAA0569, SIP-1, SMADIP1, ZEB2, Zfxlb, Zfxh1b 1558019_at —:Homo sapiens, clone IMAGE:4732650, mRNA 233551_at LOC642776: hypothetical protein LOC642776 208646_at RPS14:ribosomal protein S14 /// similar to ribosomal protein S14 208929_x_at RPL13:ribosomal protein L13 214351_x_at RPL13:ribosomal protein L13 /// similar to ribosomal protein L13 200817_x_at RPS10:ribosomal protein S10 213296_at —:Transcribed locus 213692_s_at —:— 227957_at —:— 232462_s_at FLJ23569: BC040926 227722_at RPS23:ribosomal protein S23 217466_x_at RPS2:ribosomal protein S2 /// similar to ribosomal protein S2 235534_at —:Homo sapiens, clone IMAGE: 5723825, mRNA 230741_at —:Full length insert cDNA clone YX74D05 229067_at LOC653464:Similar to SLIT-ROBO Rho GTPase- activating protein 2 (srGAP2) (Formin0binding protein 2)

TABLE 2 name matched term ANKRD44 228471_at ARHGEF19 226857_at ATPBD4 238662_at BARX2 210419_at BDNF 206382_s_at BLOC1S1 202592_at C16ORF48 223407_at C6ORF218 244829_at C8ORF13 233641_s_at CCHCR1 37425_g_at CIRBP 230142_s_at CLSTN2 219414_at COL7A1 217312_s_at DACH1 205472_s_at, 228915_at DCT 205337_at, 205338_s_at DOCK10 219279_at DRAP1 1556181_at EDNRB 204271_s_at, 206701_x_at EFNA4 205107_s_at EHD2 45297_at ETS1 224833_at FAM33A 225684_at FGFR1 210973_s_at, 211535_s_at FOXO1A 202723_s_at GGA3 209411_s_at GPR161 214104_at HIST2H2AA3 214290_s_at ID1 208937_s_at KDELR1 200922_at KIAA0738 210529_s_at KIT 205051_s_at LGR4 230674_at LHX2 (includes EG: 9355) 211219_s_at LMO4 209204_at LOC254100 1557131_at LRIG1 238339_x_at MED28 222635_s_at MKL1 215292_s_at MLANA 206426_at, 206427_s_at MLPH 218211_s_at MYEF2 222771_s_at, 232676_x_at MYO5A 227761_at NBL1 37005_at OSTM1 218196_at PDK3 221957_at PKD1 241090_at PLEKHA5 220952_s_at PLP1 210198_s_at PLXNC1 213241_at PRKCSH 200707_at PRKD3 222565_s_at PRMT1 206445_s_at PSCD3 225147_at PTPRF 200637_s_at PTPRM 1555579_s_at RAB40C 227269_s_at RASSF3 230466_s_at RHOQ 212120_at RPL13 214351_x_at RPS23 227722_at SAT1 203455_s_at, 213988_s_at, 230333_at SDCBP 200958_s_at SEC61A1 222385_x_at SEMA3C 236947_at SERGEF 232983_s_at SILV 209848_s_at SLC2A4RG 227362_at SLC7A1 212295_s_at SSBP3 217991_x_at, 223635_s_at STAM (includes EG: 8027) 203544_s_at SYNGR2 201079_at TCF7L2 (includes EG: 6934) 212759_s_at TIMM17A 215171_s_at TRIB2 202478_at TRPM1 (includes EG: 4308) 237070_at TSPAN6 209108_at TTC3 208073_x_at, 210645_s_at TUBB4 212664_at TYR 206630_at VDR 204255_s_at YIPF5 224949_at ZFHX1B 1557797_a_at, 203603_s_at 229067_at 213692_s_at 227957_at 213296_at 235534_at 233551_at 1558019_at

TABLE 3 matched term description 208073_x_at TTC3: tetratricopeptide repeat domain 3 210645_s_at TTC3: tetratricopeptide repeat domain 3 206630_at TYR: tyrosinase (oculocutaneous albinism IA) 203544_s_at STAM: signal transducing adaptor molecule (SH3 domain and ITAM motif) 1 230741_at —: Full length insert cDNA clone YX74D05

TABLE 4 matched term description 205694_at TYRP1: tyrosinase-related protein 1 206427_s_at MLANA: melan-A 206140_at LHX2: LIM homeobox 2 206630_at TYR: tyrosinase (oculocutaneous albinism IA) 203921_at CHST2: carbohydrate (N-acetylglucosamine-6-O) sulfotransferase 2 205337_at DCT: dopachrome tautomerase (dopachrome delta- isomerase, tyrosine-related protein 2) 228245_s_at OVOS2: ovostatin 2 /// similar to cDNA sequence BC048546 205338_s_at DCT: dopachrome tautomerase (dopachrome delta- isomerase, tyrosine-related protein 2) 1557797_a_at ZFHX1B: Zinc finger homeobox 1b 204271_s_at EDNRB: endothelin receptor type B 237070_at TRPM1 : transient receptor potential cation channel, subfamily M, member 1 200716_x_at RPL13A: ribosomal protein L13a 1555579_s_at PTPRM: protein tyrosine phosphatase, receptor type, M 205051_s_at KIT: v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog 200665_s_at SPARC: secreted protein, acidic, cysteine-rich (osteonectin) /// secreted protein, acidic, cysteine-rich (osteonectin) 205174_s_at QPCT: glutaminyl-peptide cyclotransferase (glutaminyl cyclase) 200725_x_at RPL10: ribosomal protein L10 232602_at WFDC3: WAP four-disulfide core domain 3 202478_at TRIB2: tribbles homolog 2 (Drosophila) 209230_s_at P8: p8 protein (candidate of metastasis 1) 232676_x_at MYEF2: myelin expression factor 2 222565_s_at PRKD3: protein kinase D3 212295_s_at SLC7A1: solute carrier family 7 (cationic amino acid transporter, y+ system), member 1 212594_at PDCD4: programmed cell death 4 (neoplastic transformation inhibitor) 218211_s_at MLPH: melanophilin 206426_at MLANA: melan-A 207065_at K6HF: cytokeratin type II 202500_at DNAJB2: DnaJ (Hsp40) homolog, subfamily B, member 2 203706_s_at FZD7: frizzled homolog 7 (Drosophila) 209969_s_at STAT1: signal transducer and activator of transcription 1, 91 kDa

TABLE 5 matched term description 205694_at tyrosinase-related protein 1 206140_at LIM homeobox 2 206427_s_at melan-A 203455_s_at spermidine/spermine N1-acetyltransferase 206453_s_at NDRG family member 2 203921_at carbohydrate (N-acetylglucosamine-6-O) sulfotransferase 2 200958_s_at syndecan binding protein (syntenin) 209283_at crystallin, alpha B 204271_s_at endothelin receptor type B 208073_x_at tetratricopeptide repeat domain 3 232602_at WAP four-disulfide core domain 3 202435_s_at cytochrome P450, family 1, subfamily B, polypeptide 1 209230_s_at p8 protein (candidate of metastasis 1) 208966_x_at interferon, gamma-inducible protein 16 205337_at dopachrome tautomerase (dopachrome delta-isomerase, tyrosine-related protein 2) 202088_at solute carrier family 39 (zinc transporter), member 6 211538_s_at heat shock 70 kDa protein 2 201556_s_at vesicle-associated membrane protein 2 (synaptobrevin 2) 241455_at Similar to AI661453 protein 237070_at transient receptor potential cation channel, subfamily M, member 1

TABLE 6 matched term description 1555505_a_at tyrosinase (oculocutaneous albinism IA) 204271_s_at endothelin receptor type B 208073_x_at tetratricopeptide repeat domain 3 200958_s_at syndecan binding protein (syntenin) 205051_s_at v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog 201245_s_at OTU domain, ubiquitin aldehyde binding 1 201603_at protein phosphatase 1, regulatory (inhibitor) subunit 12A 201605_x_at calponin 2 201908_at dishevelled, dsh homolog 3 (Drosophila) 202478_at tribbles homolog 2 (Drosophila) 1557292_a_at mucolipin 3 200601_at actinin, alpha 4 200819_s_at ribosomal protein S15 209953_s_at CDC37 cell division cycle 37 homolog (S. cerevisiae) 213146_at jumonji domain containing 3 222670_s_at v-maf musculoaponeurotic fibrosarcoma oncogene homolog B (avian) 224991_at c-Maf-inducing protein 226988_s_at myosin, heavy polypeptide 14 244829_at Hypothetical protein MGC40222

TABLE 7 matched term description 204271_s_at endothelin receptor type B 244829_at Hypothetical protein MGC40222 208073_x_at tetratricopeptide repeat domain 3 213037_x_at staufen, RNA binding protein (Drosophila) 200601_at actinin, alpha 4 219387_at KIAA1212 209168_at glycoprotein M6B 205051_s_at v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog 224991_at c-Maf-inducing protein 200613_at adaptor-related protein complex 2, mu 1 subunit 203330_s_at syntaxin 5A 225009_at chemokine-like factor superfamily 4 221485_at UDP-Gal: betaGlcNAc beta 1,4- galactosyltransferase, polypeptide 5 218255_s_at fibrosin 1 227870_at likely ortholog of mouse neighbor of Punc E11 226988_s_at myosin, heavy polypeptide 14 204086_at preferentially expressed antigen in melanoma 213146_at jumonji domain containing 3 205681_at BCL2-related protein A1 213940_s_at formin binding protein 1 202478_at tribbles homolog 2 (Drosophila) 226702_at hypothetical protein LOC129607 218402_s_at Hermansky-Pudlak syndrome 4 227099_s_at hypothetical LOC387763 218211_s_at melanophilin 217738_at pre-B-cell colony enhancing factor 1 228488_at TBC1 domain family, member 16 215695_s_at glycogenin 2 241898_at Transcribed locus, moderately similar to XP_517655.1 PREDICTED: similar to KIAA0825 protein [Pan troglodytes] 202479_s_at tribbles homolog 2 (Drosophila) 201453_x_at Ras homolog enriched in brain 228415_at Adaptor-related protein complex 1, sigma 2 subunit 201908_at dishevelled, dsh homolog 3 (Drosophila) 225600_at MRNA; cDNA DKFZp779L1068 (from clone DKFZp779L1068) 221951_at transmembrane protein 80 203455_s_at spermidine/spermine N1-acetyltransferase 201603_at protein phosphatase 1, regulatory (inhibitor) subunit 12A 1558702_at Testis expressed sequence 10 204527_at myosin VA (heavy polypeptide 12, myoxin) 235222_x_at baculoviral IAP repeat-containing 4 1560445_x_at Rho guanine nucleotide exchange factor (GEF) 1 1556205_at CDNA FLJ37227 fis, clone BRAMY2000277 226054_at bromodomain containing 4 210198_s_at proteolipid protein 1 (Pelizaeus-Merzbacher disease, spastic paraplegia 2, uncomplicated) 202370_s_at core-binding factor, beta subunit 209058_at endothelial differentiation-related factor 1 211755_s_at ATP synthase, H+ transporting, mitochondrial F0 complex, subunit b, isoform 1; ATP synthase, H+ transporting, mitochondrial F0 complex, subunit b, isoform 1 229713_at CDNA FLJ13267 fis, clone OVARC1000964 209514_s_at RAB27A, member RAS oncogene family 201299_s_at MOB1, Mps One Binder kinase activator-like 1B (yeast) 211909_x_at prostaglandin E receptor 3 (subtype EP3); prostaglandin E receptor 3 (subtype EP3) 209234_at kinesin family member 1B 207622_s_at ATP-binding cassette, sub-family F (GCN20), member 2 212421_at chromosome 22 open reading frame 9 219636_s_at armadillo repeat containing 9 223407_at chromosome 16 open reading frame 48 200645_at GABA(A) receptor-associated protein 242049_s_at neuroblastoma-amplified protein 230793_at Leucine rich repeat containing 16 215409_at PLSC domain containing protein 202984_s_at BCL2-associated athanogene 5 201864_at GDP dissociation inhibitor 1 209780_at putative homeodomain transcription factor 2 218143_s_at secretory carrier membrane protein 2 228919_at 228095_at PHD finger protein 14 213736_at Cytochrome c oxidase subunit Vb 213655_at Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, epsilon polypeptide 218419_s_at hypothetical protein MGC3123 200755_s_at calumenin 223220_s_at poly (ADP-ribose) polymerase family, member 9 237464_at LAT1-3TM protein 2 229679_at FLJ40142 protein IL-1 RI (Interleukin-1 RI) EDN2 (endothelin-2) EFNA5 (ephrin-A5) IGFBP7 (IGF Binding Protein 7) HLA-A0202 heavy chain (Human Leukocyte Antigen-A0202 heavy chain) Activin A (βA subunit) TNF RII (tumor necrosis factor receptor II) SPC4 (Subtilisin-Like Proprotein Convertase, PACE4) CNTF Rα (Ciliary neurotrophic factor receptor α)

TABLE 8 Gene Description 204271_s_at endothelin receptor type B 244829_at Hypothetical protein MGC40222 208073_x_at tetratricopeptide repeat domain 3 213037_x_at staufen, RNA binding protein (Drosophila) 200601_at actinin, alpha 4 219387_at KIAA1212 209168_at glycoprotein M6B 205051_s_at v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog 224991_at c-Maf-inducing protein 200613_at adaptor-related protein complex 2, mu 1 subunit 203330_s_at syntaxin 5A 225009_at chemokine-like factor superfamily 4 221485_at UDP-Gal: betaGlcNAc beta 1,4-galactosyltransferase, polypeptide 5 218255_s_at fibrosin 1 227870_at likely ortholog of mouse neighbor of Punc E11 226988_s_at myosin, heavy polypeptide 14 204086_at preferentially expressed antigen in melanoma 213146_at jumonji domain containing 3 205681_at BCL2-related protein A1 213940_s_at formin binding protein 1

TABLE 10 Gene Description 221750_at 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 1 (soluble) 225283_at arrestin domain containing 4 212952_at Calreticulin 226920_at Casein kinase 1, alpha 1 201533_at catenin (cadherin-associated protein), beta 1, 88 kDa 225551_at chromosome 1 open reading frame 71 227736_at chromosome 10 open reading frame 99 217883_at chromosome 2 open reading frame 25 226614_s_at chromosome 8 open reading frame 13 214073_at cortactin 233929_x_at CXYorf1-related protein 225035_x_at CXYorf1-related protein; CXYorf1-related protein; CXYorf1-related protein 200953_s_at cyclin D2 206595_at cystatin E/M 224831_at cytoplasmic polyadenylation element binding protein 4 201211_s_at DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X-linked 200762_at dihydropyrimidinase-like 2 219648_at dilute suppressor 202572_s_at discs, large (Drosophila) homolog-associated protein 4 200664_s_at DnaJ (Hsp40) homolog, subfamily B, member 1 208811_s_at DnaJ (Hsp40) homolog, subfamily B, member 6 208370_s_at Down syndrome critical region gene 1 214445_at elongation factor, RNA polymerase II, 2 214446_at elongation factor, RNA polymerase II, 2 201436_at eukaryotic translation initiation factor 4E 208290_s_at eukaryotic translation initiation factor 5 200748_s_at ferritin, heavy polypeptide 1 211628_x_at ferritin, heavy polypeptide pseudogene 1; ferritin, heavy polypeptide pseudogene 1 205409_at FOS-like antigen 2 200959_at fusion (involved in t(12; 16) in malignant liposarcoma) 201065_s_at general transcription factor II, i; general transcription factor II, i, pseudogene 1 218238_at GTP binding protein 4 201841_s_at heat shock 27 kDa protein 1 225988_at hect domain and RLD 4 241683_at HECT domain containing 1 201944_at hexosaminidase B (beta polypeptide) 219976_at hook homolog 1 (Drosophila) 213079_at hypothetical protein DT1P1A10 215434_x_at hypothetical protein FLJ20719; AG1 protein 1569157_s_at hypothetical protein LOC162993 227052_at Hypothetical protein LOC201895 225065_x_at hypothetical protein MGC40157 231733_at ICEBERG caspase-1 inhibitor 240941_at Intersectin 2 208881_x_at isopentenyl-diphosphate delta isomerase 1 204615_x_at isopentenyl-diphosphate delta isomerase 1 213507_s_at karyopherin (importin) beta 1 203068_at kelch-like 21 (Drosophila) 225142_at KIAA1718 protein 220368_s_at KIAA2010 1559226_x_at late cornified envelope 1E 1559224_at late cornified envelope 1E 200673_at lysosomal-associated protein transmembrane 4 alpha 223480_s_at mitochondrial ribosomal protein L47 207121_s_at mitogen-activated protein kinase 6 214939_x_at myeloid/lymphoid or mixed-lineage leukemia (trithorax homolog, Drosophila); translocated to, 4 203315_at NCK adaptor protein 2 230291_s_at Nuclear factor I/B 211467_s_at nuclear factor I/B 213032_at Nuclear factor I/B 223650_s_at nuclear receptor binding factor 2 222878_s_at OTU domain, ubiquitin aldehyde binding 2 217608_at p18 splicing regulatory protein 200907_s_at palladin 202290_at PDGFA associated protein 1 218942_at phosphatidylinositol-4-phosphate 5-kinase, type II, gamma 225147_at pleckstrin homology, Sec7 and coiled-coil domains 3 216515_x_at prothymosin, alpha (gene sequence 28); hypothetical gene supported by BC013859; hypothetical gene supported by BC013859; BC070480 200773_x_at prothymosin, alpha (gene sequence 28); similar to prothymosin alpha; hypothetical gene supported by BC013859; hypothetical gene supported by BC013859; BC070480 212099_at ras homolog gene family, member B 212124_at retinoic acid induced 17 200022_at ribosomal protein L18; ribosomal protein L18 201909_at ribosomal protein S4, Y-linked 1 215127_s_at RNA binding motif, single stranded interacting protein 1 218143_s_at secretory carrier membrane protein 2 205185_at serine peptidase inhibitor, Kazal type 5 1554089_s_at Shwachman-Bodian-Diamond syndrome; Shwachman- Bodian-Diamond syndrome pseudogene 208991_at signal transducer and activator of transcription 3 (acute-phase response factor) 224573_at similar to DNA segment, Chr 11, Brigham & Womens Genetics 0434 expressed 242687_at Similar to RIKEN cDNA 9930021J17 206675_s_at SKI-like 1553602_at small breast epithelial mucin 213879_at SMT3 suppressor of mif two 3 homolog 2 (yeast) 208738_x_at SMT3 suppressor of mif two 3 homolog 2 (yeast); similar to SMT3 suppressor of mif two 3 homolog 2 1556839_s_at Spectrin, beta, non-erythrocytic 5 220983_s_at sprouty homolog 4 (Drosophila); sprouty homolog 4 (Drosophila) 205966_at TAF13 RNA polymerase II, TATA box binding protein (TBP)-associated factor, 18 kDa 217733_s_at thymosin, beta 10 216438_s_at thymosin, beta 4, X-linked; thymosin-like 3 226835_s_at transaldolase 1; similar to RPE-spondin 224680_at transmembrane emp24 protein transport domain containing 4 210987_x_at tropomyosin 1 (alpha) 211702_s_at ubiquitin specific peptidase 32; ubiquitin specific peptidase 32 203798_s_at visinin-like 1 210935_s_at WD repeat domain 1 224905_at WD repeat domain 26 215150_at YOD1 OTU deubiquinating enzyme 1 homolog (yeast) 227309_at YOD1 OTU deubiquinating enzyme 1 homolog (yeast) 204180_s_at zinc finger protein 297B 219163_at zinc finger protein 562 220854_at 224051_at 224050_s_at

TABLE 11 Gene Description 225519_at protein phosphatase 4, regulatory subunit 2 219199_at AF4/FMR2 family, member 4 203450_at PKD2 interactor, golgi and endoplasmic reticulum associated 1 213729_at formin binding protein 3 220748_s_at zinc finger protein 580 216480_x_at Myeloid/lymphoid or mixed-lineage leukemia (trithorax homolog, Drosophila); translocated to, 10 200043_at enhancer of rudimentary homolog (Drosophila); enhancer of rudimentary homolog (Drosophila) 211075_s_at CD47 antigen (Rh-related antigen, integrin-associated signal transducer); CD47 antigen (Rh-related antigen, integrin-associated signal transducer) 1555945_s_at chromosome 9 open reading frame 10 212295_s_at solute carrier family 7 (cationic amino acid transporter, y+ system), member 1 212687_at LIM and senescent cell antigen-like domains 1 224714_at MKI67 (FHA domain) interacting nucleolar phosphoprotein 218768_at nucleoporin 107 kDa 228196_s_at La ribonucleoprotein domain family, member 5 217836_s_at YY1 associated protein 1 212620_at zinc finger protein 609 226845_s_at myeloma overexpressed 2 200747_s_at nuclear mitotic apparatus protein 1 242304_at within bgcn homolog (Drosophila) 204767_s_at flap structure-specific endonuclease 1 217869_at hydroxysteroid (17-beta) dehydrogenase 12 222729_at F-box and WD-40 domain protein 7 (archipelago homolog, Drosophila) 201776_s_at KIAA0494 1552658_a_at neuron navigator 3 1555972_s_at F-box protein 28 216242_x_at DNA directed RNA polymerase II polypeptide J-related gene 231505_s_at Sideroflexin 4 228738_at hypothetical protein MGC25181 228942_s_at DAB2 interacting protein 208959_s_at thioredoxin domain containing 4 (endoplasmic reticulum) 223407_at chromosome 16 open reading frame 48 1555278_a_at cytoskeleton associated protein 5 219375_at choline/ethanolamine phosphotransferase 1 208728_s_at cell division cycle 42 (GTP binding protein, 25 kDa) 50376_at zinc finger protein 444 243108_at RAN binding protein 9 212884_x_at Apolipoprotein E 65630_at transmembrane protein 80 214953_s_at amyloid beta (A4) precursor protein (peptidase nexin-II, Alzheimer disease) 223946_at cofactor required for Sp1 transcriptional activation, subunit 3, 130 kDa 232926_x_at ankyrin repeat domain 19 203597_s_at WW domain binding protein 4 (formin binding protein 21) 223601_at olfactomedin 2 212365_at myosin IB 203297_s_at Jumonji, AT rich interactive domain 2 231019_x_at Serine/threonine kinase 11 (Peutz-Jeghers syndrome) 201291_s_at topoisomerase (DNA) II alpha 170 kDa 211846_s_at poliovirus receptor-related 1 (herpesvirus entry mediator C; nectin) 226843_s_at PAP associated domain containing 5 225243_s_at sarcolemma associated protein 236651_at kalirin, RhoGEF kinase 214792_x_at vesicle-associated membrane protein 2 (synaptobrevin 2) 228922_at Src homology 2 domain containing F 225537_at trafficking protein particle complex 6B 46665_at sema domain, immunoglobulin domain (Ig), transmembrane domain (TM) and short cytoplasmic domain, (semaphorin) 4C 209702_at fatso 203358_s_at enhancer of zeste homolog 2 (Drosophila) 211310_at enhancer of zeste homolog 1 (Drosophila) 242767_at LIM and cysteine-rich domains 1 1555575_a_at KDEL (Lys-Asp-Glu-Leu) endoplasmic reticulum protein retention receptor 1 223151_at DCN1, defective in cullin neddylation 1, domain containing 5 (S. cerevisiae) 204170_s_at CDC28 protein kinase regulatory subunit 2 229420_at Luminal binding protein 1 (BiP-1) (BP1) 202355_s_at general transcription factor IIF, polypeptide 1, 74 kDa 206061_s_at Dicer1, Dcr-1 homolog (Drosophila) 224597_at Transcribed locus, strongly similar to XP_523650.1 PREDICTED: similar to keratin 17 [Pan troglodytes] 217739_s_at pre-B-cell colony enhancing factor 1 218943_s_at DEAD (Asp-Glu-Ala-Asp) box polypeptide 58 211087_x_at mitogen-activated protein kinase 14; mitogen- activated protein kinase 14 220193_at chromosome 1 open reading frame 113 229410_at progestagen-associated endometrial protein (placental protein 14, pregnancy-associated endometrial alpha- 2-globulin, alpha uterine protein) 221844_x_at CDNA clone IMAGE: 6208446 227683_x_at Nudix (nucleoside diphosphate linked moiety X)-type motif 4 pseudogene 2 233621_s_at Rho guanine nucleotide exchange factor (GEF) 12 214270_s_at microtubule-associated protein, RP/EB family, member 3 217762_s_at RAB31, member RAS oncogene family 231271_x_at HSCARG protein 227330_x_at similar to hypothetical protein MGC27019 209773_s_at ribonucleotide reductase M2 polypeptide 225227_at SKI-like 218428_s_at REV1-like (yeast) 201556_s_at vesicle-associated membrane protein 2 (synaptobrevin 2)

TABLE 12 Gene Description 1552477_a_at interferon regulatory factor 6 228707_at claudin 23 206427_s_at melan-A 218196_at osteopetrosis associated transmembrane protein 1 219142_at RAS-like, family 11, member B 200601_at actinin, alpha 4 226483_at transmembrane protein 68 243568_at Glycine-rich protein (GRP3S) 212382_at Transcription factor 4 218417_s_at hypothetical protein FLJ20489 208905_at cytochrome c, somatic 203753_at transcription factor 4 244535_at Forkhead box P1 222243_s_at transducer of ERBB2, 2 205174_s_at glutaminyl-peptide cyclotransferase (glutaminyl cyclase) 231851_at hypothetical protein FLJ10770 200961_at selenophosphate synthetase 2 210880_s_at embryonal Fyn-associated substrate 230986_at Kruppel-like factor 8 229689_s_at Discs, large homolog 5 (Drosophila) 204319_s_at regulator of G-protein signalling 10 219842_at ADP-ribosylation factor related protein 2 224560_at TIMP metallopeptidase inhibitor 2 208758_at 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase 238662_at similar to RIKEN cDNA 5730421E18 gene 214000_s_at Regulator of G-protein signalling 10 1559360_at Nuclear RNA-binding protein, putative 205694_at tyrosinase-related protein 1 231579_s_at TIMP metallopeptidase inhibitor 2 238967_at Claudin 1 222146_s_at transcription factor 4 230748_at solute carrier family 16 (monocarboxylic acid transporters), member 6; similar to solute carrier family 16, member 6; monocarboxylate transporter 6

TABLE 13 Sample Melanoma Melanoma Melanoma Melanoma Melanoma gene description DT357-M DT330-M DT359-M DT419-M DT407-M 244829_at C6orf218 114.5632 19.56224 0.594604 7.412704 53.81737 204271_s_at EDNRB 225.972 151.1671 18.89588 16.67945 754.8258 200601_at ACTN4 30.90996 23.10287 10.05611 1.484524 60.96883 226988_s_at MYH14 0.192109 0.343885 0.032804 0.140632 0.009486 202478_at TRIB2 99.73307 75.58353 28.84001 12.72858 464.6498 1557292_a_at MCOLN3 28.05138 8.282119 5.464161 4.084049 64.89341 224991_at CMIP 0.615572 0.208772 0.214641 0.205898 0.115023 1555505_a_at TYR 21.25897 23.26356 9.849155 0.952638 150.1229 201908_at DVL3 0.339151 0.088388 0.239816 8.111676 5.502167 222670_s_at MAFB 0.070316 0.069348 0.005263 0.00146 0.532185 201605_x_at CNN2 150.1229 58.48521 15.13692 13.54793 324.0337 213146_at JMJD3 0.005048 0.003879 0.02683 0.00198 0.009486 201603_at PPP1R12A 2.188587 4.69134 0.817902 0.281265 7.361501 209953_s_at CDC37 12.72858 34.05985 4.756828 0.615572 13.73705 201245_s_at OTUB1 9.063071 6.233317 5.464161 1.905276 10.77787 208073_x_at TTC3 15.34823 12.72858 8.168097 8.224911 36.50444 200958_s_at SDCBP 3.07375 1.197479 0.336808 0.078021 6.916298 205051_s_at KIT 86.82268 54.1917 2.713209 8.815241 55.71524 200819_sat RPS15 1584.707 1640.591 491.1432 182.2784 3795.305 Sample Melanoma Melanoma Melanoma Melanoma Melanoma gene description DT412-M DT403-M DT406-M DT356-M DT405-M 244829_at C6orf218 0.456916 16.44982 10884.59 17.14838 2797.65 204271_s_at EDNRB 17.26765 81.00842 45073.75 63.11889 11828.67 200601_at ACTN4 5.241574 38.85424 4269.94 9.000468 13682.08 226988_s_at MYH14 0.554785 0.004613 1 0.164938 1045.516 202478_at TRIB2 15.67072 19.42712 1 24.93327 14972.21 1557292_a_at MCOLN3 3.555371 3.24901 1067.485 4.756828 1082.386 224991_at CMIP 1.741101 1.148698 1 0.122428 1351.176 1555505_a_at TYR 5.426417 2.928171 4870.992 2.732081 3468.269 201908_at DVL3 4.924578 1.292353 32.89964 4.169863 7281.399 222670_s_at MAFB 0.164938 0.145592 1 0.000816 103.9683 201605_x_at CNN2 17.5087 28.44297 22226.61 32.67239 46340.95 213146_at JMJD3 0.001211 0.018326 37.01402 0.078563 50.91433 201603_at PPP1R12A 0.05954 0.926588 481.0356 0.103665 205.0739 209953_s_at CDC37 2.732081 21.70567 1226.218 7.310652 9410.137 201245_s_at OTUB1 1.580083 11.87619 3691.522 1.840375 4182.066 208073_x_at TTC3 6.916298 7.674113 4973.342 1.741101 4299.64 200958_s_at SDCBP 0.065154 0.389582 261.3791 0.5 247.2797 205051_s_at KIT 4.055838 0.435275 3082.745 12.81712 689.7836 200819_sat RPS15 377.4129 1884.544 389158.9 484.3815 668236.8

TABLE 14 Sample Nevus Nevus Nevus Nevus Nevus gene description DF543 DF544 DT343 DT342 DT344 244829_at C6orf218 0.094732 0.80107 0.297302 0.00849 0.000905 204271_s_at EDNRB 393.44 16 401.7071 0.135842 0.010598 200601_at ACTN4 0.289172 44.3235 5712.87 65.79928 12.21007 226988_s_at MYH14 0.094732 1.404445 430.539 48.50293 0.109576 202478_at TRIB2 23.26356 6.868523 797.8645 0.00849 0.005601 1557292_a_at MCOLN3 0.25 0.882703 0.297302 0.00849 0.000905 224991_at CMIP 3.944931 0.664343 132.5139 7.727491 0.61132 1555505_a_at TYR 2.297397 9.189587 0.297302 0.00849 0.010167 201908_at DVL3 0.094732 2.219139 139.1021 0.993092 0.248273 222670_s_at MAFB 0.233258 1.006956 41.93259 1.879045 0.112656 201605_x_at CNN2 41.93259 183.5463 21027.65 855.13 50.91433 213146_at JMJD3 0.094732 0.496546 4.69134 0.07911 0.000905 201603_at PPP1R12A 0.094732 3.680751 85.03589 19.02731 0.543367 209953_s_at CDC37 1.918528 8.815241 699.4126 34.5353 0.959264 201245_s_at OTUB1 0.094732 11.87619 1663.493 45.25483 11.08088 208073_x_at TTC3 0.882703 58.08123 1478.583 12.295 0.132127 200958_s_at SDCBP 0.094732 0.188156 3.317278 0.986233 0.016402 205051_s_at KIT 0.094732 0.239816 34.5353 2.602684 0.011203 200819_s_at RPS15 13124.73 4299.64 205674 11346.82 584.071 Sample Nevus Nevus Nevus Nevus Nevus gene description DT345 DT427 DT337 DT340 DT338 244829_at C6orf218 1 0.550953 0.939523 0.001236 0.479632 204271_s_at EDNRB 225.972 1136.199 0.20733 0.001236 393.44 200601_at ACTN4 14462.21 3350.127 127.1158 64.44516 3236.009 226988_s_at MYH14 2304.12 867.0672 2.907945 1.265757 410.1478 202478_at TRIB2 1 8422.308 4.287094 3.434262 12.46663 1557292_a_at MCOLN3 1 116.9704 14.12325 0.001236 0.479632 224991_at CMIP 1686.714 369.6459 1.021012 1.918528 433.5336 1555505_a_at TYR 63.55792 10.33882 1.94531 0.001236 39.67065 201908_at DVL3 404.5012 1097.496 6.588728 1.580083 9.38268 222670_s_at MAFB 418.7659 12.64066 0.946058 0.002577 51.98415 201605_x_at CNN2 3615.551 10015.87 181.0193 58.48521 3821.703 213146_at JMJD3 1.580083 0.550953 0.628507 0.001236 0.479632 201603_at PPP1R12A 16.22335 202.2506 3.160165 0.008373 942.2722 209953_s_at CDC37 2957.167 94.35323 60.54769 7.110741 3929.146 201245_s_at OTUB1 9026.807 10297.45 47.50475 9.063071 2179.83 208073_x_at TTC3 6472.018 1937.526 50.56264 0.314253 2836.704 200958_s_at SDCBP 7.568461 0.550953 0.346277 0.001236 1.049717 205051_s_at KIT 1 37.01402 1.22264 0.001236 0.479632 200819_s_at RPS15 736333.6 137588.5 7967.989 600.4915 269513.9

TABLE 15 Lentigo Solar (Lentigo Maligna lentigo Maligna)/(Solar Mean Mean Lentigo) Gene expression expression fold change Description 200961_at 455.88 223.03 2.04 selenophosphate synthetase 2 200782_at 379.88 70.68 5.37 annexin A5 206427_s_at 1899.38 165.82 11.45 melan-A 217998_at 416.81 99.94 4.17 pleckstrin homology-like domain, family A, member 1 226602_s_at 117.73 209.24 0.56 breakpoint cluster region; similar to breakpoint cluster region isoform 1 240366_at 70.62 6.65 10.62 Lipoma HMGIC fusion partner-like 3 208325_s_at 760.50 1233.35 0.62 A kinase (PRKA) anchor protein 13 225202_at 196.73 24.59 8.00 Rho-related BTB domain containing 3 225946_at 46.81 5.74 8.16 Ras association (RalGDS/AF-6) domain family 8 1553603_s_at 37.15 61.18 0.61 ADP-ribosylation factor-like 6 interacting protein 2 220625_s_at 125.23 75.62 1.66 E74-like factor 5 (ets domain transcription factor) 229982_at 28.00 20.79 1.35 hypothetical protein FLJ21924 1552283_s_at 17.50 35.56 0.49 zinc finger, DHHC-type containing 11 200723_s_at 203.23 113.68 1.79 membrane component, chromosome 11, surface marker 1 209174_s_at 57.35 106.44 0.54 FLJ20259 protein 233599_at 244.31 403.97 0.60 Chromosome 9 open reading frame 3 201739_at 4791.23 2597.32 1.84 serum/glucocorticoid regulated kinase 209392_at 403.54 12.79 31.54 ectonucleotide pyrophosphatase/ phosphodiesterase 2 (autotaxin) 209487_at 185.54 46.44 4.00 RNA binding protein with multiple splicing 221653_x_at 882.08 458.24 1.92 apolipoprotein L, 2 209185_s_at 349.73 118.85 2.94 insulin receptor substrate 2 222809_x_at 227.73 336.12 0.68 chromosome 14 open reading frame 65 223363_at 150.69 280.06 0.54 hypothetical protein MGC10911 208456_s_at 56.19 122.65 0.46 related RAS viral (r-ras) oncogene homolog 2 221449_s_at 69.81 41.09 1.70 T-cell immunomodulatory protein; T-cell immunomodulatory protein 215268_at 24.12 46.74 0.52 KIAA0754 protein 217188_s_at 146.88 397.50 0.37 chromosome 14 open reading frame 1 236972_at 302.00 27.09 11.15 tripartite motif-containing 63

TABLE 16 solar solar solar solar solar solar solar solar solar solar solar solar lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo DF529- DF530- DF633- DF634- DF635- DF636- DF637- DF638- DF639- DF640- DF641- DF642- gene S S S S S S S S S S S S 200961_at 106 217 101 38 161 221 160 336 304 256 63 210 200782_at 122 21 45 8 70 27 104 195 200 63 101 114 206427_s_at 58 28 92 19 132 29 92 72 1708 12 92 190 217998_at 106 67 180 18 86 76 181 95 238 169 7 8 226602_s_at 654 97 144 691 129 265 109 194 137 277 194 130 240366_at 6 6 7 6 5 6 27 6 6 6 6 6 225202_at 5 6 22 9 84 14 13 14 35 8 21 5 225946_at 5 5 5 5 6 5 5 5 13 6 5 5 1553603_s_at 33 70 60 5 67 59 40 26 54 127 21 43 220625_s_at 37 35 6 6 17 173 55 29 42 5 13 5 229982_at 58 17 25 9 15 13 22 17 9 33 16 12 1552283_s_at 14 31 38 14 49 10 14 33 19 23 41 13 200723_s_at 94 159 201 22 263 94 299 157 95 217 75 93 209174_s_at 118 143 64 25 107 89 103 236 46 256 38 110 233599_at 89 322 294 116 433 380 295 370 306 241 252 294 201739_at 1421 958 3724 618 2023 2741 3098 4062 3856 1907 1530 1569 209392_at 7 44 6 19 10 9 9 10 47 6 17 17 209487_at 6 403 9 6 16 6 24 163 94 5 5 23 221653_x_at 88 379 298 349 396 575 322 372 3571 319 1159 1349 209185_s_at 307 365 182 58 86 140 195 127 44 97 165 130 222809_x_at 646 253 322 6 358 262 319 316 490 277 381 654 223363_at 206 112 192 102 324 318 343 323 185 694 706 860 208456_s_at 322 22 30 34 83 22 125 71 129 125 43 122 221449_s_at 35 26 73 7 69 31 51 37 8 52 66 49 215268_at 11 12 43 9 30 8 22 8 44 73 11 51 217188_s_at 1276 36 545 12 519 479 281 801 209 500 99 457 236972_at 6 6 6 11 6 6 6 6 12 6 6 13

TABLE 17 solar solar solar solar solar solar solar solar solar solar solar solar lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo DF643- DT024- DT055- DT069- DT079- DT123- DT146- DT187- DT306- DT365- DT367- DT368- gene S S S S S S S S S S S S 200961_at 223 149 159 8 113 202 2155 152 177 56 76 180 200782_at 17 79 6 84 136 8 5 95 65 34 29 11 206427_s_at 9 444 5 13 29 7 11 500 672 5 6 20 217998_at 15 178 8 104 181 64 6 62 31 205 42 16 226602_s_at 286 212 327 97 368 456 57 84 154 301 50 24 240366_at 6 6 6 7 6 6 6 6 6 6 6 6 208325_s_at 1565 923 877 30 973 1508 1981 1326 1289 863 354 3194 225202_at 49 40 8 9 21 101 8 47 22 12 31 8 225946_at 5 6 5 6 6 5 5 5 9 5 5 6 1553603_s_at 54 72 76 21 84 84 44 71 80 71 100 168 220625_s_at 118 5 6 5 5 14 865 17 5 5 6 6 229982_at 8 8 13 8 33 6 16 18 22 13 13 18 1552283_s_at 10 23 9 11 12 9 13 155 122 10 13 67 200723_s_at 32 21 21 7 179 50 220 171 93 92 17 83 209174_s_at 172 38 48 85 256 115 110 147 109 141 27 96 233599_at 594 125 489 243 695 36 931 591 623 1648 346 1044 201739_at 3963 4104 8062 2767 2729 2760 378 2524 1236 3566 2237 785 209392_at 8 8 7 10 10 7 7 35 14 7 9 7 209487_at 39 139 6 7 84 12 201 44 8 19 6 6 221653_x_at 330 198 139 243 341 331 301 382 511 137 564 306 209185_s_at 53 83 133 7 201 137 170 91 84 78 32 86 222809_x_at 323 478 622 65 190 729 938 438 211 284 180 249 223363_at 196 291 109 85 163 290 331 165 279 161 145 234 208456_s_at 43 211 509 472 81 24 298 32 69 19 75 231 221449_s_at 121 78 31 6 39 10 46 74 56 60 6 31 215268_at 36 19 18 8 102 119 104 133 24 14 108 27 217188_s_at 692 225 228 11 480 1467 195 178 306 423 29 189 236972_at 6 34 6 17 5 6 6 6 6 6 7 6

TABLE 18 solar solar solar solar solar solar solar solar solar solar lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo gene DT369-S DT370-S DT371-S DT372-S DT373-S DT409-S DT414-S DT422-S DT459-S DT460-S 200961_at 55 39 38 124 262 37 881 60 128 136 200782_at 139 50 248 17 73 48 117 11 53 8 206427_s_at 9 92 20 7 625 9 585 19 7 20 217998_at 496 34 123 58 140 71 22 31 98 182 226602_s_at 123 46 107 349 95 97 184 440 119 117 240366_at 6 6 6 6 6 6 6 6 6 6 208325_s_at 1373 60 557 201 1500 2266 1545 1500 2099 839 225202_at 20 12 9 122 9 8 5 11 40 8 225946_at 6 6 6 6 6 5 5 6 6 5 1553603_s_at 57 101 22 34 47 33 47 39 102 68 220625_s_at 5 6 5 6 6 5 974 6 11 67 229982_at 58 6 13 13 13 8 13 31 117 13 1552283_s_at 65 12 18 9 15 6 87 138 25 81 200723_s_at 95 97 11 41 97 77 253 7 103 329 209174_s_at 177 31 140 123 28 163 134 13 47 84 233599_at 453 300 195 152 58 166 802 300 279 273 201739_at 2723 3494 2757 850 3680 3553 721 897 3544 3472 209392_at 6 9 31 7 7 7 12 10 9 7 209487_at 15 6 7 6 6 6 166 7 23 6 221653_x_at 237 204 353 362 354 249 229 108 171 353 209185_s_at 100 15 10 82 94 6 496 13 101 73 222809_x_at 167 215 248 121 408 209 336 138 226 369 223363_at 121 145 83 121 984 182 227 150 466 229 208456_s_at 168 41 216 39 230 22 77 23 28 134 221449_s_at 34 6 5 10 7 160 18 7 27 61 215268_at 88 9 11 52 55 13 24 9 254 40 217188_s_at 647 119 93 79 122 694 269 111 834 910 236972_at 6 36 619 8 11 6 6 17 5 6

TABLE 19 lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo maligna maligna maligna maligna maligna maligna maligna maligna maligna maligna maligna DF569- DF557- DF579- DF580- DF582- DF596- DF623- DF624- DF625- DF626- DF627- gene LM LM LM LM LM LM LM LM LM LM LM 200961_at 847 567 158 531 234 359 357 330 347 518 1667 200782_at 154 500 157 193 764 1310 331 27 157 161 16 206427_s_at 1833 2805 95 1327 2219 6320 3253 49 274 193 121 217998_at 185 1245 726 88 907 773 789 182 340 114 10 226602_s_at 49 47 59 51 71 36 50 51 137 91 579 240366_at 139 251 6 43 122 35 15 6 12 25 6 208325_s_at 20 1362 725 408 882 430 568 1583 1867 1460 699 225202_at 25 16 44 312 237 1183 170 33 26 83 8 225946_at 48 57 9 76 12 7 35 5 5 6 28 1553603_s_at 8 21 43 67 45 21 37 38 50 23 10 220625_s_at 5 5 5 288 29 5 132 154 126 206 1427 229982_at 8 8 19 8 28 21 13 44 35 28 93 1552283_s_at 11 14 12 16 5 13 68 10 35 13 13 200723_s_at 159 480 276 85 369 112 349 90 319 242 134 209174_s_at 135 24 48 68 87 130 40 58 85 110 60 233599_at 158 60 524 126 283 385 298 183 228 276 165 201739_at 6073 10285 3008 5935 4757 3159 3792 3462 3128 2916 826 209392_at 772 235 14 1088 210 243 912 9 8 8 7 209487_at 291 148 21 315 280 1146 521 31 16 71 61 221653_x_at 433 203 613 743 1224 5336 983 425 227 141 43 209185_s_at 1935 1458 124 482 85 535 182 98 169 308 154 222809_x_at 33 32 55 45 161 31 36 437 163 170 1483 223363_at 161 136 139 92 156 129 114 241 122 147 105 208456_s_at 20 27 27 21 49 57 8 33 39 210 46 221449_s_at 7 7 28 54 30 50 199 185 57 24 156 215268_at 9 11 157 41 17 11 42 11 27 9 9 217188_sat 8 8 94 11 148 39 8 1146 455 62 107 236972_at 1318 1977 6 137 77 247 51 8 31 6 13

TABLE 20 lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo lentigo maligna maligna maligna maligna maligna maligna maligna maligna maligna maligna maligna maligna DF629- DF630- DF631- DF632- DT017- DT266- DT268- DT269- DT270- DT331- DT355- DT423- gene LM LM LM LM LM LM LM LM LM LM LM LM 200961_at 350 139 465 196 510 439 435 383 744 306 398 420 200782_at 291 156 265 8 551 52 255 33 825 469 1914 308 206427_s_at 2834 317 1121 5 4173 290 1952 181 3873 3913 9382 990 217998_at 307 241 427 38 521 285 328 48 1470 344 879 184 226602_s_at 114 46 230 74 48 184 81 280 13 46 30 107 240366_at 6 6 6 6 6 43 8 8 115 262 642 47 208325_s_at 529 101 448 1404 956 506 782 632 608 2658 396 642 225202_at 139 152 36 66 143 121 83 46 1987 65 23 31 225946_at 6 6 81 6 28 14 32 9 415 46 202 67 1553603_s_at 34 40 21 32 52 13 37 37 22 56 11 37 220625_s_at 5 6 69 95 11 23 33 90 5 6 6 239 229982_at 36 14 56 47 29 13 21 13 12 13 12 12 1552283_s_at 13 12 10 10 16 10 13 9 38 26 34 13 200723_s_at 321 300 70 118 138 68 21 54 80 97 67 113 209174_s_at 84 52 12 40 38 26 84 70 28 47 63 29 233599_at 296 32 96 80 1338 115 314 86 131 497 62 235 201739_at 2421 3869 4568 3885 2679 4995 4927 4514 12929 5385 9033 5005 209392_at 273 223 464 11 656 26 498 7 1581 287 2683 238 209487_at 101 6 338 6 661 1 9 36 6 366 33 243 90 221653_x_at 626 873 983 336 1599 265 780 493 516 1548 1540 437 209185_s_at 389 115 164 214 105 201 102 255 1272 161 139 160 222809_x_at 166 105 461 83 125 527 435 453 22 186 56 322 223363_at 314 122 132 90 191 105 206 373 167 113 167 104 208456_s_at 17 26 122 27 44 203 61 36 71 22 27 196 221449_s_at 36 171 107 142 39 74 48 83 11 10 40 162 215268_at 11 7 9 9 43 11 24 16 8 11 11 98 217188_s_at 175 638 24 79 138 166 95 50 8 144 25 84 236972_at 33 34 328 7 365 41 51 9 1766 698 421 200

TABLE 21 lentigo lentigo lentigo maligna maligna maligna gene DT425-LM DT461-LM DF523-LM 200961_at 798 348 7 200782_at 150 328 502 206427_s_at 177 778 909 217998_at 38 233 135 226602_s_at 492 49 46 240366_at 6 9 6 208325_s_at 20 38 49 225202_at 68 9 9 225946_at 5 6 6 1553603_s_at 168 21 22 220625_s_at 204 6 76 229982_at 58 62 25 1552283_s_at 13 18 10 200723_s_at 863 24 335 209174_s_at 49 12 12 233599_at 93 53 238 201739_at 2997 4238 5786 209392_at 20 9 10 209487_at 6 6 6 221653_x_at 750 1089 728 209185_s_at 273 7 6 222809_x_at 111 35 188 223363_at 107 83 102 208456_s_at 22 10 40 221449_s_at 22 22 51 215268_at 6 6 13 217188_s_at 38 6 63 236972_at 8 7 13

Although the invention has been described with reference to the above examples, it will be understood that modifications and variations are encompassed within the spirit and scope of the invention. Accordingly, the invention is limited only by the following claims. 

What is claimed:
 1. A method for non-invasive analysis of a skin sample, the method comprising: obtaining a skin sample collected using at least one adhesive tape, wherein the adhesive tape comprises: an adhesive matrix on a first surface of a collection area; and a skin sample adhered to the adhesive matrix, wherein the adhesive tape comprises a demarcation indicative of a region to be processed; removing the demarcated region from the collection area; and analyzing one or more target genes in the removed region of the collection area comprising the skin sample.
 2. The method of claim 1, wherein the demarcation is representative of an outline of a skin lesion.
 3. The method of claim 2, wherein the demarcation is approximately 1 millimeter from the outline of the skin lesion.
 4. The method of claim 2, wherein the demarcation is created by a surgical skin marker or a water soluble marker.
 5. The method of claim 1, wherein the demarcation comprises marker on a second surface of the collection area.
 6. The method of claim 1, wherein the collection area comprises a transparent material.
 7. The method of claim 1, wherein the skin sample is collected using a plurality of adhesive tapes.
 8. The method of claim 1, wherein the analyzing comprises detection of RNA and/or DNA.
 9. The method of claim 1, further comprising deriving information related to a disease wherein the deriving is based on the quantified expression levels of the one or more target genes.
 10. The method of claim 9, wherein the disease comprises a cancer.
 11. The method of claim 9, wherein the information related to the disease comprises an identification of a disease state, a likelihood of treatment success for a disease state, an identification of progression of a disease state, or an identification of a disease stage.
 12. The method of claim 1, further comprising providing a strip, wherein the adhesive matrix comprising the skin sample is placed onto the strip with the skin sample facing down.
 13. The method of claim 12, wherein the strip is stored at −20 degrees Celsius prior to analysis.
 14. The method of claim 1, wherein the demarcation is made by a user.
 15. The method of claim 14, wherein the user is a patient.
 16. The method of claim 1, wherein the skin sample comprises at least 200 μg of RNA.
 17. The method of claim 1, wherein the analyzing comprises quantifying expression levels of the one or more target genes.
 18. The method of claim 1, wherein the removing comprises cutting the demarcated region from the collection area.
 19. A method for non-invasive collection and analysis of a skin sample, the method comprising: receiving an adhesive skin sample collection kit comprising at least one adhesive tape, wherein the adhesive tape comprises: an adhesive matrix on a first surface of a collection area; and a skin sample adhered to the adhesive matrix, wherein the adhesive tape comprises a demarcation indicative of a region to be processed; and quantifying expression levels of one or more target genes in the skin sample; wherein any one of (i)-(iii): (i) wherein the demarcation is representative of an outline of a skin lesion, and the demarcation is approximately 1 millimeter from the outline of the skin lesion, (ii) the method further comprising providing an adhesive strip, wherein the adhesive matrix comprising the skin sample is placed onto the adhesive strip with the skin sample facing down, or (iii) wherein the demarcation is representative of an outline of a skin lesion, and the demarcation is created by a surgical skin marker or a water soluble marker.
 20. The method of claim 19, wherein the demarcation is representative of an outline of a skin lesion, and the demarcation is approximately 1 millimeter from the outline of the skin lesion.
 21. The method of claim 19, comprising providing an adhesive strip, wherein the adhesive matrix comprising the skin sample is placed onto the adhesive strip with the skin sample facing down.
 22. The method of claim 21, wherein the adhesive strip is stored at −20 degrees Celsius prior to analysis.
 23. The method of claim 19, wherein the demarcation is representative of an outline of a skin lesion, and the demarcation is created by a surgical skin marker or a water soluble marker. 